Experimental investigations on effects of tool flank wear on surface integrity during orthogonal dry cutting of Ti-6Al-4V

Machining titanium alloy Ti-6Al-4V is a challenging task since tool flank wear adversely affects surface integrity. Quantitative effects of predetermined tool flank wear values (VB) on the surface integrity were investigated through the orthogonal dry cutting of Ti-6Al-4V. Experimental results indicated that three-dimensional (3D) average surface roughness increased with the VB ranging from 0 to 0.2 mm but decreased at VB = 0.3 mm. Given the effects of rubbing and ironing enhanced, surface material burning and plastic flows emerged on the machined surface at VB = 0.3 mm. Not only the plastic deformation layer became deeper but also the grains were greatly distorted with the increase of tool flank wear. When machined by using the tool at VB = 0.3 mm, the β phase of Ti-6Al-4V decreased near the machined surface layer than that of using the fresh tool. Besides, the depth of work-harden layer increased from 20 to 60 μm with the VB increasing from 0 to 0.3 mm. The softened layer was generated near the machined surface by using the tool at VB = 0.3 mm. In addition, the residual compressive stresses of the machined surface had the trend of decreasing. Experimental results indicated that the VB less than 0.2 mm was the most suitable condition for better surface integrity during orthogonal dry cutting of Ti-6Al-4V. This study aims at providing experimental data for optimizing the processing parameters and improving the surface integrity of Ti-6Al-4V.     

Effect of the process parameters on the three-dimensional shape of molten pool during full-penetration laser welding process

Slow tool servo (STS) turning is superior in machining precision and in complicated surface. However, STS turning is a complex process in which many variables can affect the desired results. This paper focuses on surface roughness prediction in lenses STS turning. An exponential model, based on the five main cutting parameters including tool nose radius, feed rate, depth of cut, C-axis speed, and discretization angle, for surface roughness prediction of lenses is developed by means of orthogonal experiment regression analysis. Meanwhile, a prediction model of surface roughness based on least squares support vector machines (LS-SVM) with radial basis function is constructed. Orthogonal experiment swatches are studied, and chaotic particle swarm optimization and leave-one-out cross-validation are applied to determine the model parameters. The comparison of LS-SVM model and exponential model is also carried out. Predictive LS-SVM model is found to be capable of better predictions for surface roughness and has absolute fraction of variance R² of 0.99887, the mean absolute percent error e_M of 8.96 %, and the root mean square error e_R of 10.68 %. The experimental results and prediction of LS-SVM model show that effects of tool nose radius and feed rate are more significant than that of depth of cut on surface roughness of lenses turning.     

Lubricity of High Water Content Aqueous Gels

Aqueous gels such as biopolymer gels, mucus, and high water content hydrogels are often qualitatively described as lubricious. In hydrogels, mesh size, ξ, has been found to be a controlling parameter in friction coefficient. In the tribology of aqueous gels, we suggest that the Weissenberg number (Wi) is a useful parameter to define different regimes, and following the original formulations in rheology, Wi is given by the polymer relaxation time (ηξ³/k_BT) multiplied by the shear rate due to fluid shear through a single mesh (V/ξ): Wi?=?ηVξ²/k_BT. At sliding speeds below a Weissenberg number of approximately 0.1, Wi?<?0.1, the friction coefficient is velocity-independent and scales with mesh size to the ??1 power, µ ∝ ξ^?1. De Gennes’ scaling concepts for elastic modulus, E, give a dependence on polymer mesh size to the ??3 power, E ∝ ξ^?3, and following Hertzian contact analysis, the contact area is found to depend on the mesh size squared, A ∝ ξ². Combining these concepts, the shear stress, τ, and therefore the lubricity of aqueous gels, is predicted to be highly dependent on the mesh size, τ ∝ ξ^?3. Studies aimed at elucidating the fundamental mechanism of lubricity in biopolymer gels, mucus, and hydrogels have wrestled with comparisons across mesh size, which can be extremely difficult to accurately quantify. Using scaling concepts relating polymer mesh size to water content reveals that shear stress decreases rapidly with increasing water content, and plots of shear stress as a function of swollen water content are suggested as a useful method to compare aqueous gels of unknown mesh size. As a lower bound, these data are compared against estimates of fluid shear stress for free and bound water flowing through a mesh size estimated by the water content of the gels. The results indicate that the strong dependence on lubricity is likely due to a synergistic combination of a low viscosity solvent (water) coupled to a system that has a decreasing friction coefficient, modulus, and the resulting contact pressure with increasing water content. Although the permeability, K, of aqueous gels increases dramatically with water content (and mesh size), K ? ξ²/η, the stronger decrease of the elastic modulus and subsequent decrease in contact pressure due to an increase in the contact length, predicts that the draining time under contact, t, actually increases strongly with increasing water content and mesh size, t ∝ ξ². Consistent with the finding of extremely high water content aqueous gels on the surfaces of biological tissues, these high water content gels are predicted to be optimal for lubrication as they are both highly lubricious and robust at resisting draining and sustaining hydration.     

Determination of a coupling equation for milling parameters based on optimal cutting temperature

Nanofluid minimum quantity lubrication (NMQL) is one of the main modes of sustainable manufacturing. It is an environment-friendly, energy-saving, and highly efficient lubrication method. With the use of nanoparticles, the tribological properties of debris–tool and workpiece–tool interfaces will change. However, spectrum analyses of force and power spectral density (PSD) of surface microstructures are limited. In the present work, the milling force, friction coefficient, specific energy, surface roughness, and surface microstructure of debris were evaluated in milling of 45 steel for different lubrication conditions, namely, dry, flood, minimum quantity lubrication, and Al₂O₃ NMQL. Results demonstrated that compared with other lubrication conditions, NMQL achieves minimum milling force peak (F_x?=?270 N, F_y?=?160 N, F_z?=?50 N), friction coefficient (μ?= 1.039), specific energy (U?= 65.5 J/mm³), and surface roughness value (R_a?=?2.254 μm, RS_m?=?0.0562 mm). Furthermore, a spectrum analysis of the milling force and PSD of the surface microstructure was conducted for validation. The spectral analysis of milling force revealed that NMQL obtained the lowest milling force and amplitude in the middle-frequency region, thereby indicating the minimum abrasion loss of the tool. Meanwhile, the PSD analysis indicated that NMQL had the lowest proportional coefficient in the low-frequency region (0.4766) and the highest proportional coefficient in the high-frequency region (0.0569). These results revealed that the workpiece surface gained by Al₂O₃ NMQL obtained higher wave fineness than other working conditions. By combining with the lowest R_a, NMQL contributes the best workpiece surface quality. Therefore, machining experiments using NMQL showed the best lubrication performance.     

Calculation of negative-pressure chip in suction-type internal chip removal system and analysis of influencing factors

Compacted graphite iron (CGI) is considered as the ideal material to make modern fuel-efficient diesel engine. Due to the vermicular or worm-like graphite distributed among the ferrite/pearlite matrix, CGI behaves better physical and mechanical properties in comparison with gray cast iron (GCI) and spherical graphite spheroidal cast iron (SGI). However, these good properties bring about the machining challenges. So it is important to appropriately select cutting parameters to machine this material with economy and efficiency. The present study investigated the influence of cutting parameters, such as cutting speed V, feed rate f, and exit angle Ψ, on workpiece material removal volume Q and cutting burr height on the entrance side H₁ and on the exit side H₂ during high-speed milling of CGI by the coated carbide tools_. On this basis, the relatively optimum high-speed cutting parameters were selected under the research condition. Cutting tool failure mechanism was also investigated with the aid of scanning electronic microscope (SEM) and energy-dispersive system (EDS) (SUPRA55, Germany) analysis. The results showed that Q, H₁, H₂, and the type of cutting burr on the exit side of the machined surface could be influenced by the cutting parameters. And the relatively optimum cutting parameters are V = 800 m/min, f = 0.25 mm/rev, and Ψ = 60°. Adhesive wear and thermal cracks which were perpendicular to the cutting edge were common wear mechanisms during the cutting process. However, with an increase in feed rate, mechanical cracks which were parallel to the cutting edge could be found on the flank face of the cutting tool.     

Investigate on milling force of cryogenic cooling processing aluminum honeycomb treated by ice fixation

Aerospace metal honeycomb materials with low stiffness had often the deformation, burr, collapse, and other defects in the mechanical processing. They were attributed to poor fixation method and inapposite cutting force. This paper presented the improvement of fixation way. The hexagonal aluminum honeycomb core material was treated by ice fixation, and the NC milling machine was used for a series of cryogenic machining. Considering the similar structure of fiber-reinforced composite materials, the milling force prediction model of ice fixation aluminum honeycomb was established, considering tool geometry parameters and cutting parameters. Meanwhile, the influence rule on milling force was deduced. The results show that compared with the conventional fixation milling method, the honeycomb processing effect is improved greatly. The machining parameters affect order on milling forces: the cutting depth is the most important, followed by the cutting width, then the spindle speed and the feed. Moreover, too small cutting depth (a_p?=?0.5 mm) will cause insufficient cutting force, while a_p?>?2 mm with higher force will reduce the processing quality of honeycomb. Simultaneously, the honeycomb orientation (θ) has a great influence on processing quality. Using the model, the predicted and measured error values of the feed and main cutting force are all small in θ?<?90°. But, the rate is 33 and 26% for the main cutting force and feed force error in θ?>?90°, respectively, while they all exhibit the smallest error in θ?=?60°. This bigger error mainly is due to unstable cutting force with obtuse angle. In addition, the tool rake angle has little influence on cutting quality in θ?<?90°, but bigger on that in θ?>?90°. Furthermore, the calculation model successfully conforms to the main deformation mechanism and influences parameters of the cutting force in the milling process, and it can accurately predict the cutting force in θ?<?90° and guide the milling process.     

Parametric optimization of CNC turning process for hybrid metal matrix composite

Machining of hybrid metal matrix composite is difficult as the particulates are abrasive in nature and they behave like a cutting edge during machining resulting in quick tool wear and induces vibration. An attempt was made in this experimental study to evaluate the machining characteristics of hybrid metal matrix composite, and a mathematical model was developed to predict the responses, namely surface finish, intensity of vibration and work-tool interface temperature for known cutting condition while machining was performed in computer numerical control lathe. Design of experiments approach was used to conduct the trials; response surface methodology was employed to formulate a mathematical model. The experimental study inferred that the vibration in V _x, V _y, and V _z were 41.59, 45.17, and 26.45 m/s², respectively, and surface finish R _a, R _q, and R _z were 1.76, 3.01, and 11.94 μm, respectively, with work-tool interface temperature ‘T’ of 51.74 °C for optimal machining parameters, say, cutting speed at 175 m/min, depth of cut at 0.25 mm and feed rate at 0.1 mm/rev during machining. Experimental results were in close conformity with response surface method overlay plot for responses.     

Effect of Oxygen on the Self-formation of Carbonaceous Tribo-layer with Carbon Nitride Coatings under a Nitrogen Atmosphere

The ball-on-disk friction and wear tests of CN _X coatings (CN _X /CN _X ) were conducted under a nitrogen atmosphere with controlled relative humidity (RH) (3.4–40.0%RH) and oxygen concentration (100–21 × 10⁴ ppm) in this study. We found that the specific wear rate of CN _X coating on ball (W _b), which could give stable and low friction coefficient (<0.05), was below 3.0 × 10^?8 mm³/Nm. Average friction coefficients (µ _a) and W _b of CN _X /CN _X increased (µ _a: 0.02–0.33, W _b: 1.6 × 10^?8–2.4 × 10^?7 mm³/Nm) with increasing oxygen concentration (230–211,000 ppm) as well as RH (4.7–21.1%RH) under a nitrogen atmosphere. However, the W _b remained low value below 2.3 × 10^?8 mm³/Nm regardless of oxygen concentration (100–207,000 ppm) of a nitrogen atmosphere (3.4–3.9%RH) when CN _X -coated balls were slid against a hydrogenated CN _X (CN _X :H) coatings (CN _X /CN _X :H). Besides, the CN _X /CN _X :H achieved low and stable friction coefficient below 0.05 under a nitrogen atmosphere (10,000 ppmO₂) regardless of increasing RH up to 20%RH. Raman analysis indicated that the structure of carbon on the top surface of CN _X coating was changed from as-deposited CN _X coating in the case of low friction coefficient (<0.05). Furthermore, TOF-SIMS analysis provided the evidence that the carbon derived from CN _X -coated disk was considered to diffuse into the ball surface, and it mixed with the carbon derived from CN _X -coated ball on the wear scar, which formed the chemically bonded carbon tribo-layer. Low friction coefficient (<0.05) with CN _X coatings under a nitrogen atmosphere was achieved due to self-formation of the carbon tribo-layer.     

Manufacturing and mechanical characterization of Al<Subscript>2</Subscript>O<Subscript>3</Subscript>/β-TCP/TiO<Subscript>2</Subscript> biocomposite as a potential bone substitute

This paper focuses on the mechanical characterization of a bioceramic based on commercial alumina (Al₂O₃) mixed with synthesized tricalcium phosphate (β-TCP) and commercial titania powder (TiO₂). The effect of β-TCP and TiO₂ addition on the mechanical performance was investigated. After a sintering process at 1600 °C for 1 h, various mechanical properties of the samples have been studied, such as compressive strength, flexural strength, tensile strength, elastic modulus, and fracture toughness. The measurements of the elastic modulus (E) and the tensile strength (σ _t ) were conducted using the modified Brazilian test while the compressive strength (σ _c ) was determined through a compression test. Also, semi-circular bending (SCB) specimens were used to evaluate the flexural strength (σ _f ) and the opening mode fracture toughness (K _IC). From the main results, it was found that the best mechanical performance is obtained with the addition of 10 wt.% TCP and 5 wt.% TiO₂. Alumina/10 wt.% tricalcium phosphate/5 wt.% titania composites displayed the highest values of mechanical properties and a good combination of compressive strength (σ _c ?≈?352 MPa), flexural strength (σ _f ?≈?98 MPa), tensile strength (σ _t ?≈?86.65 MPa), and fracture toughness (K _IC?≈?13 MPa m^1/2).     

Big data analysis of a mini three-axis CNC machine tool based on the tuning operation of controller parameters

The characteristic responses of a mini three-axis computer numerical control (CNC) machine tool based on the controller tuning operation were investigated for big data estimation. The major tuning parameters included the position control gains K _p, the position feed-forward control gains K _f, the speed control gains K _v, and the gain ratios K _g of the position and speed control values in manufacturing industries. K _p gains of 10, 30, 50, 80, 100, 200, 300, and 400 rad/s, K _f gains of 0, 30, 50, 60, 80, and 100 %, K _v gains of 30, 50, 70, 100, 300, 900, 2000, and 3000 rad/s, and K _g ratios of (1:1), (3:1), (5:1), and (7:1) were analyzed for smart productivity. The results show that the settling times at different K _p values were almost constant when the K _p gain was over 200 rad/s. The maximum overshoots, when the feed-forward gain is over 60 %, almost increased with increasing feed-forward gains. However, the overshoot of the three-axis CNC machine tool decreased as the K _v gain increased until the K _v gain reached 70 rad/s. The settling times at a constant K _g ratio decreased with an increase in the K _p and K _v gains. The characteristic responses of the tuning operations were enabled with connectivity to a cloud network to share the big data, to support decision making, and to adjust operations in real time.     

Taguchi-based grey relational analysis for modeling and optimizing machining parameters through dry turning of Incoloy 800H

The present research focused on the optimization of machining parameters and their effects by dry-turning an incoloy 800H on the basis of Taguchi-based grey relational analysis. Surface roughness (Ra, Rq and Rz), cutting force (Fz), and cutting power (P) were minimized, whereas Material removal rate (MRR) was maximized. An L ₂₇ orthogonal array was used in the experiments, which were conducted in a computerized and numerical-controlled turning machine. Cutting speed, feed rate, and cut depth were set as controllable machining variables, and analysis of variance was performed to determine the contribution of each variable. We then developed regression models, which ultimately conformed to investigational and predicted values. The combinational parameters for the multiperformance optimization were V = 35 m/min, f = 0.06 mm/rev and a = 1 mm, which altogether correspond to approximately 48.98 % of the improvement. The chip morphology of the incoloy 800H was also studied and reported.     

Improvement of AA5052 sheet properties by electromagnetic twin-roll casting

Although servo scanning 3D micro electro discharge machining (SS-3D MEDM) can achieve a high discharge ratio, the processing efficiency is still lower than expected because the discharge area at micro-electrode tip is much smaller than the area to machine. In particular, for 3D micro cavities, the processing efficiency and the machining accuracy inherently contradict each other. In this paper, an on-machine process of rough-and-finishing SS-3D MEDM is proposed with consideration that most cavity material cannot affect the dimensional accuracy. In the rough machining process, technological measures such as high discharge energy and large-diameter tool electrodes are applied to maximize processing efficiency. In the finishing machining process, a small amount of material is removed for dimensional accuracy, smooth surface, and clear edges-and-corners by changing multi-factors of machining parameters. The research is concentrated on two key techniques: rough-and-finishing border strategy and micro tool-electrode precision measurement for the process transformation from rough to finishing. Moreover, an online measurement method is proposed by the point electric contact between a micro electrode and a standard thin-rod, and the measurement accuracy was up to ±1 µm in our experimental system. Machining experiments of 3D micro cavities < 800 µm verified the proposed methods and the processes including 3D model design, rough-machining, micro-electrode measurement and fabrication, and finishing machining. The experimental results were successfully achieved as follows: the dimensional accuracy < 5 µm, surface roughness Sa0.38 µm, and the processing efficiency being improved to 2.4 times.     

Sustainability analyses of cutting edge radius on specific cutting energy and surface finish in side milling processes

The aim of this work is to determine the influence of cutting edge radius on the specific cutting energy and surface finish in a mechanical machining process. This was achieved by assessing the direct electrical energy demand during side milling of aluminium AW6082-T6 alloy and AISI 1018 steel in a dry cutting environment using three different cutting tool inserts. The specific energy coefficient was evaluated as an index of the sustainable milling process. The surface finish of the machined parts was also investigated after machining. It was observed that machining with the 48.50-μm cutting edge radius insert resulted in lower specific cutting energy requirements when compared with the 68.50 and 98.72-μm cutting edge radii inserts, respectively. However, as the ratio of the undeformed chip thickness to cutting edge radius is less than 1, the surface roughness increases. The surface roughness values gradually decrease as the ratio of undeformed chip thickness to cutting edge radius (h/r _e) tends to be 1 and at minimum surface roughness values when the ratio of h/r _e equalled to 1. However, the surface roughness values increased as h/r _e becomes higher than 1. This machining strategy further elucidates the black box and trade-offs of ploughing and rubbing characteristics of micro machining and optimization strategy for minimum energy and sustainable manufacture.     

Optimization of flux-cored arc welding process parameters by using genetic algorithm

The effect of flux-cored arc welding (FCAW) process parameters on the quality of the super duplex stainless steel (SDSS) claddings can be studied using Taguchi L9 design of experiments. In this experimental investigation, deposits were made with 30 % bead overlap. Establishing the optimum combination of process parameters is required to ensure better bead geometry and desired properties. The above objectives can be achieved by identifying the significant input process parameters as input to the mathematical models like welding voltage (X ₁), wire feed rate (X ₂), welding speed (X ₃), and nozzle-to-plate distance (X ₄). The identified responses governing the bead geometry are bead width (W) and height of the reinforcement (H). The mathematical models were constructed using the data collected from the experiments based on Taguchi L9 orthogonal array. Then, the responses were optimized using non-traditional nature-inspired technique like genetic algorithm (GA).     

Integrated ANN-LWPA for cutting parameter optimization in WEDM

In this paper, we present a new approach to determinate cutting parameters in wire electrical discharge machining (WEDM), integrated artificial neuron network (ANN), and wolf pack algorithm based on the strategy of the leader (LWPA). The cutting parameters considered in this paper are pulse-on, current, water pressure, and cutting feed rate. Models of the effects of the four parameters on machining time (T_p), machining cost (C_p), and surface roughness (Ra) are mathematically constructed. An ANN-LWPA integration system with multiple fitness functions is proposed to solve the modelling problem. By using the proposed approach, this study demonstrates that T_p, C_p, and Ra can be estimated at 164.1852 min, 239.5442 RMB, and 1.0223 μm in single objective optimization, respectively. For example, as for Ra, integrated ANN-LWPA has optimized the Ra value by the reduction of 0.1337 μm (11.6 %), 0.3377 μm (24.8 %), and 0.105 μm (10.3 %) compared to experimental data, regression model, and ANN model, respectively. Consequently, the ANN-LWPA integration system boasts some advantages over decreasing the value of fitness functions by comparison with the experimental regression model, ANN model, and conventional LWPA result. Moreover, the proposed integration system can be also utilized to obtain multiple solutions by uniform design-based exploration. Therefore, in order to solve complex machining optimization problems, an intelligent process scheme could be integrated into the numeric control system of WEDM.     

Soft computing models and intelligent optimization system in electro-discharge machining of SiC/Al composites

In this paper, a multi-variable regression model, a back propagation neural network (BPNN) and a radial basis neural network (RBNN) have been utilized to correlate the cutting parameters and the performance while electro-discharge machining (EDM) of SiC/Al composites. The four cutting parameters are peak current (I_p), pulse-on time (T_on), pulse-off time (T_off), and servo voltage (S_v); the performance measures are material remove rate (MRR) and surface roughness (Ra). By testing a large number of BPNN architectures, 4-5-1 and 4-7-1 have been found to be the optimal one for MRR and Ra, respectively; and it can predict them with 10.61 % overall mean prediction error. As for RBNN architectures, it can predict them with 12.77 % overall mean prediction error. The multivariable regression model yields an overall mean prediction error of 13.93 %. All of these three models have been used to study the effect of input parameters on the material remove rate and surface roughness, and finally to optimize them with genetic algorithm (GA) and desirability function. Then, an intelligent optimization system with graphical user interface (GUI) has been built based on these multi-optimization techniques, in which users can obtain the optimized cutting parameters under the desired surface roughness (Ra).     

Laser decoating of DLC films for tribological applications

Damaged DLC coatings usually require remanufacturing of the entire coated components starting from an industrial chemical de-coating step. Alternatively, a complete or local coating repair can be considered. To pursue this approach, however, a local coating removal is needed as first operation. In this context, controlled decoating based on laser sources can be a suitable and clean alternative to achieve a pre-fixed decoating depth with high accuracy. In the present study, we investigated a laser-based decoating process executed on multilayered DLC films for advanced tribological applications (deposited via a hybrid PVD/PE-CVD technique). The results were acquired via multifocal optical digital microscopy (MF-ODM), which allowed high-resolution 3D surface reconstruction as well as digital profilometry of the lasered and unlasered surface. The study identifies the most critical process parameters which influence the effective decoating depth and the post-decoating surface roughness. In particular, the role of pulse overlap (decomposed along orthogonal directions), laser fluence, number of lasing passes and assist gas is discussed in text. A first experimental campaign was designed to identify the best conditions to obtain full decoating of the DLC + DLC:Cr layers. It was observed that decreasing the marking speed to 200 mm/s was necessary to obtain a sufficient pulse overlap and a nearly planar ablation profile. By operating with microsecond pulses and 1 J/cm² (fairly above the ablation threshold), less than 10 passes were needed to obtain full decoating of the lasered area with an etching rate of 1.1 μm/loop. Further experiments were then executed in order to minimise the roughness of the rest surface with the best value found at around 0.2 μm. Limited oxidation but higher R _a values were observed in Ar atmosphere.     

Experimental study on micro electrical discharge machining of porous stainless steel

Various cutter strategies have been developed during milling freeform surface. Proper selection of the cutter path orientation is extremely important in ensuring high productivity rate, meeting the better quality level, and longer tool life. In this work, finish milling of TC17 alloy has been done using carbide ball nose end mill on an incline workpiece angle of 30°. The influence of cutter path orientation was examined, and the cutting forces, tool life, tool wear, and surface integrity were evaluated. The results indicate that horizontal downward orientation produced the highest cutting forces. Vertical downward orientation provided the best tool life with cut lengths 90–380 % longer than for all other orientations. Flank wear and adhesion wear were the primary wear form and wear mechanisms, respectively. The best surface finish was achieved using an upward orientation, in particular, the vertical upward orientation. Compressive residual stresses were detected on all the machined surfaces, and vertical upward orientation provided the minimum surface compressive residual stress. In the aspect of tool wear reduction and improvement of surface integrity, horizontal upward cutter path orientation was a suitable choice, which provided a tool life of 270 m, surface roughness (R _a ) of 1.46 μm, and surface compressive residual stress of ?300 MPa.     

Impact of aspect ratio and surface heating on pollutant transport in street canyons

This paper investigated the impacts of surface heating on pollutant transport and Air Exchange Rate (AER) in street canyons of different aspect ratios (building heightH to street widthW) using computational fluid dynamic (CFD) technique. Street canyons ofH/W varied from 0.1 to 2 were employed in the study. These street-canyon aspect ratios covered a range of basic flow regimes including skimming flow (H/W=1 and 2), wake interference flow (H/W=0.5), and isolated roughness flow (H/W=0.1). Different façade/surface heating imposed different influence on the flow field and pollutant transport in street canyons of differentH/W. The AER induced by vertical velocity fluctuationAER _w, and mean vertical velocityAER _w . AER of street canyon with differentH/W and different surface heating exhibited their unique characteristics.     

Geometry simulation and evaluation of the surface topography in five-axis ball-end milling

Limited by the factors such as dynamic vibrations, cutting heat, and the use of coolant, it is difficult to measure or evaluate the surface quality in real time. Geometry simulation of the surface topography became the main method used in engineering to estimate and control the quality of the surface machining. This paper proposed a new method for geometry simulation and evaluation of a milled surface. Allowing for the coherency in geometric variations management process, the proposed method is developed based on the skin model of a workpiece. To make the simulated surface topography more realistic, the effects of locating errors, spindle errors, geometrical errors of the machine tool, and cutting tool deflections are included. And a new method is adopted to evaluate the milled surface, in which the roughness of the surface is characterized by the modal coefficients, instead of the R _a , R _z , and R _q values. At the end of this paper, measurements and cutting tests are carried out to validate the proposed method.