Numerical and experimental study on the effect of vibration of the tool in ultrasonic assisted EDM

In this paper the effect of ultrasonic vibration of the tool in the process of electrical discharge machining is investigated. The ultrasonic vibration of the tool has significant effect on the dynamic behaviour of the vapour bubble generated between the tool and the workpiece due to the electrical discharge. The computational simulation of the bubble behaviour is carried out by employing the boundary integral equation method. Results show that when the electrical discharge occurs in the closest position of the tool to the workpiece, the vapour bubble expands to the largest maximum volume of the bubble and the lifetime of the bubble is the longest. This in turn makes the pressure inside the bubble decrease rapidly to the lowest magnitude and causes melted material at the sparked point vaporize and leave the crater on the surface of the workpiece.     

X-Ray Absorption Spectroscopy and Morphology Study on Antiwear Films Derived from ZDDP Under Different Sliding Frequencies

X-ray absorption near-edge structure (XANES) spectroscopy has been used to characterize the chemistry of antiwear (AW) films generated from mineral base oil containing a zinc dialkyl dithiophosphate additive. These films were formed on rubbed steel surfaces with a reciprocating boundary contact using different sliding frequencies. The phosphorus L-edge XANES spectra show that these films have slightly different chemical natures. Longer chain polyphosphates were present on the steel surface prepared at the higher sliding frequencies. The surface morphology of these films was investigated using atomic force microscopy. These images show that the surface morphology of the AW films changes with the sliding frequency. Round and bigger antiwear pads were formed at a lower frequency while higher frequencies resulted in thinner films and flattened surfaces. Nanomechanical properties of these antiwear films were investigated by nanoindentation measurement and the elastic moduli extracted from force–displacement (f–d) curves are similar for all antiwear films, 100 ± 10 GPa.     

Simple fiber-optic confocal microscopy with nanoscale depth resolution beyond the diffraction barrier

A novel fiber-optic confocal approach for ultrahigh depth-resolution (相似文献   

Magnetic field effect on fluid flow characteristics in a pipe for laminar flow

The influence of a magnetic field on the skin friction factor of steady fully-developed laminar flow through a pipe was studied experimentally. A mathematical model was introduced and a finite difference scheme used to solve the governing equations in terms of vorticity-stream function. The model predictions agree favourably with experimental results. It is observed that the pressure drop varies in proportion to the square of the product of the magnetic field and the sine of the magnetic field angle. Also, the pressure drop is proportional to the flow rate. This situation is similar to what applies in the absence of a magnetic field. It is found that a transverse magnetic field changes the axial velocity profile from the parabolic to a relatively flat shape. At first, the radial velocity rises more rapidly and then gradually decreases along the pipe until falling to zero. A numerical correlation can be written for the considerable distance required for the new axial velocity profile to establish. Owing to the changes taking place in the axial velocity profile, it exhibits a higher skin friction factor. The new axial velocity profile asymptotically approaches its limit as the Hartmann number becomes large.     

Morphological,Electrical, and Chemical Changes in Cyclically Contacting Polycrystalline Silicon Surfaces Coated with Perfluoroalkylsilane Self-Assembled Monolayer

The evolution of morphology, electrical properties, and chemical composition has been studied in cyclically contacting polycrystalline silicon (polysilicon) surfaces coated with perfluoroalkylsilane self-assembled monolayer (SAM). The microinstrument used is a MEMS cantilever that is repeatedly actuated out-of-plane to impact a landing pad and is then moved in-plane to enable nondestructive in situ inspection of the impacted area. Analyses show that a device with a monolayer coating exhibits signs of surface degradation after a much higher number of cycles than its uncoated counterpart. A sharp increase in contact resistance between the cantilever and landing pad is observed at ~10 billion cycles for a coated device, versus ~25 million cycles for an uncoated device. Likewise, the onset of grain fracture in the landing pad occurs at ~25 billion cycles for the SAM-coated device, versus ~3 billion cycles for its uncoated counterpart. The effectiveness of the monolayer coating diminishes after more than 100 billion contact cycles as the SAM layer is removed, and the polysilicon substrate becomes susceptible to adhesive wear.     

Solving a bi-objective cell formation problem with stochastic production quantities by a two-phase fuzzy linear programming approach

We propose a bi-objective cell formation problem with demand of products expressed in a number of probabilistic scenarios. To deal with the uncertain demand of products, a framework of two-stage stochastic programming model is presented. The proposed model considers minimizing the sum of the miscellaneous costs (machine constant cost, expected machine variable cost, cell fixed-charge cost, and expected intercell movement cost) and expected total cell loading variation. Because of conflicting objectives, we develop a two-phase fuzzy linear programming approach for solving bi-objective cell formation problem. To show the effectiveness of the proposed approach, numerical examples are solved and the results are compared with the two existing approaches in the literature. The computational results show that the proposed fuzzy method achieves lower objective functions as well as higher satisfaction degrees.     

Networked control of industrial automation systems—a new predictive method

A new method for real-time prediction of uncertain network transmission time delays and a method for closed-loop control of manufacturing and industrial plants through networks are introduced. The proposed delay prediction method is based on the multilayer perceptron neural model. In order to minimize the number of neurons in the first layer of the network and hence reducing the computational burden in a real-time implementation, a method for determination of the Markov order of the time delay sequence is presented. Using the predicted delay, and a zero-order hold equivalent discrete-time model of the plant, a time varying state feedback control algorithm with a real-time gain updating strategy is proposed. A sufficient condition for closed-loop stability is also derived using the switching theorem for linear systems. The proposed method is shown, through two industrial networked case studies, namely, a DC motor driving a transportation roller for paper sheets and a milling machine. Simulation studies depict the efficacy of the proposed method in controlling such challenging problems.     

A novel two-stage genetic algorithm for a mixed-model U-line balancing problem with duplicated tasks

A widespread supposition on mixed-model assembly line-balancing problems assigns a task, which is shared between two or more models to a single station. Bukchin and Rabinowitch (European Journal of Operational Research, 174:492–508, 2006) relaxed the restriction for mixed-model straight-line assembly line problems and allowed tasks common to multiple models to be assigned to different stations, called task duplication. In this paper, considering the same relaxation but for mixed-model U-shaped assembly lines, a novel genetic algorithm (GA) approach for solving large-scale problems is developed. Although superiorities of U-shaped assembly lines over straight lines have been discussed in several articles, this paper makes the advantage more tangible by providing a quantitative example. This paper also presents a novel two-stage genetic algorithm which is fittingly devised for solving the new proposed model. In order to evaluate the effectiveness of the GA, one small-scale and one medium-scale problem are solved using both the proposed GA and Lingo 8.0 software, and the obtained outcomes are compared. The computational results indicate that the GA is capable of providing high-quality solutions for small- and medium-scale problems in negligible central processing unit (CPU) times. It is worth mentioning that, for large-scale problems, such as Kim and Arcus test problems, no analogous results for those obtained by our proposed GA exist. To conclude, it can be said that the proposed GA performs well and is able to solve large-scale problems within acceptable CPU times.     

Online monitoring of transit-time ultrasonic flowmeters based on fusion of optical observation

It is well-known that transit-time ultrasonic flowmeters (TTUF) are unsuitable for bubble-contained flows. This paper presents a new online monitoring method based on optical observation, which monitors the functionality of the TTUF in the presence of bubbles in the fluid. The method avoids the unnecessary Emergency Shutdowns (ESD) due to bubble presence in the fluid by bubble detection. The proposed method accomplishes bubble identification through a combination of image processing and wavelet analysis. In addition, a new method is proposed which estimates single bubble size in horizontal pipes using a data fusion approach.     

Neuro-fuzzy control strategy for an offshore steel jacket platform subjected to wave-induced forces using magnetorheological dampers

Magnetorheological (MR) damper is a prominent semi-active control device to vibrate mitigation of structures. Due to the inherent non-linear nature of MR damper, an intelligent non-linear neuro-fuzzy control strategy is designed to control wave-induced vibration of an offshore steel jacket platform equipped with MR dampers. In the proposed control system, a dynamic-feedback neural network is adapted to model non-linear dynamic system, and the fuzzy logic controller is used to determine the control forces of MR dampers. By use of two feedforward neural networks required voltages and actual MR damper forces are obtained, in which the first neural network and the second one acts as the inverse dynamics model, and the forward dynamics model of the MR dampers, respectively. The most important characteristic of the proposed intelligent control strategy is its inherent robustness and its ability to handle the non-linear behavior of the system. Besides, no mathematical model needed to calculate forces produced by MR dampers. According to linearized Morison equation, wave-induced forces are determined. The performance of the proposed neuro-fuzzy control system is compared with that of a traditional semi-active control strategy, i.e., clipped optimal control system with LQG-target controller, through computer simulations, while the uncontrolled system response is used as the baseline. It is demonstrated that the design of proposed control system framework is more effective than that of the clipped optimal control scheme with LQG-target controller to reduce the vibration of offshore structure. Furthermore, the control strategy is very important for semi-active control.