Development of empirical model for abrasive wear volume of sisal fibre–epoxy composites

Abstract

In this paper, an empirical model was developed for high stress abrasive wear behaviour of unidirectional sisal fibre reinforced epoxy composites under varying operating parameters, for which a number of experiments were carried out to determine the abrasive wear behaviour of the composites. Polysulphide modified epoxy resin was used to make composites having three different sisal fibre concentrations in three different fibre orientations, namely longitudinal, transverse and normal. Abrasive wear of composites depends on operating parameters, such as applied load, grit size, sliding distance and weight percentage of sisal fibre. The abrasive wear data have been analysed using statistical analysis, and empirical relations are proposed.     

Assessment of a turbulence model for numerical predictions of sheet-cavitating flows in centrifugal pumps?

Various approaches have been developed for numerical predictions of unsteady cavitating turbulent flows. To verify the influence of a turbulence model on the simulation of unsteady attached sheet-cavitating flows in centrifugal pumps, two modified RNG k-? models (DCM and FBM) are implemented in ANSYS-CFX 13.0 by second development technology, so as to compare three widespread turbulence models in the same platform. The simulation has been executed and compared to experimental results for three different flow coefficients. For four operating conditions, qualitative comparisons are carried out between experimental and numerical cavitation patterns, which are visualized by a high-speed camera and depicted as isosurfaces of vapor volume fraction α _v = 0.1, respectively. The comparison results indicate that, for the development of the sheet attached cavities on the suction side of the impeller blades, the numerical results with different turbulence models are very close to each other and overestimate the experiment ones slightly. However, compared to the cavitation performance experimental curves, the numerical results have obvious difference: the prediction precision with the FBM is higher than the other two turbulence models. In addition, the loading distributions around the blade section at midspan are analyzed in detail. The research results suggest that, for numerical prediction of cavitating flows in centrifugal pumps, the turbulence model has little influence on the development of cavitation bubbles, but the advanced turbulence model can significantly improve the prediction precision of head coefficients and critical cavitation numbers.     

Evaluation of thermal deformation model for BGA packages using moiré interferometry

A compact model approach of a network of spring elements for elastic loading is presented for the thermal deformation analysis of BGA package assembly. High-sensitivity moiré interferometry is applied to evaluate and calibrated the model quantitatively. Two ball grid array (BGA) package assemblies are employed for moiré experiments. For a package assembly with a small global bending, the spring model can predict the boundary conditions of the critical solder ball excellently well. For a package assembly with a large global bending, however, the relative displacements determined by spring model agree well with that by experiment after accounting for the rigid-body rotation. The shear strain results of the FEM with the input from the calibrated compact spring model agree reasonably well with the experimental data. The results imply that the combined approach of the compact spring model and the local FE analysis is an effective way to predict strains and stresses and to determine solder damage of the critical solder ball.     

The efficiency of a hypoid axle—a thermally coupled lubrication model

The final drive unit in road vehicles, such as medium and heavy trucks, and four-wheel-drive and rear-wheel-drive passenger cars, usually consists of a hypoid or spiral bevel geared transmission and differential, housed in a self-contained, dip-lubricated axle. Such units are subjected to very variable duty—including extreme combinations of speed, gradient, applied torque and external temperature—and are typically cooled by natural and forced convection on the exterior surface. On the other hand, there are appreciable internal power losses due to gear friction and churning and to bearing and seal losses. These losses are highly dependent upon the lubrication regime of the internal components and hence to the thermal behaviour of the entire axle.In the present paper, we describe a thermally coupled model of axle lubrication. The torque and speed demand is first found from a specified duty (“drive cycle”) which includes terrain as well as speed-versus-time and external temperature data. The evolution of sump oil and component temperatures is followed, and increments of energy loss evaluated in each time-step. Elastohydrodynamic film thickness is determined for the hypoid gear set, using a development of Buckingham's method, and friction losses calculated using a simple oil rheological model based on tribometer (MTM) testing. Churning, seal and bearing (speed-dependent) losses are found using empirical algorithms. Energy losses over complete drive cycles for different lubricants are derived, enabling the relative fuel economy for different oils to be evaluated.Results show that (i) the bulk temperature rise of the axle is highly dependent on the specified vehicle duty and (ii) the efficiency can be strongly influenced by choices available to the lubricant formulator. Taken together, these findings suggest that specialist axle lubricant formulations for particular vehicle types and applications will be attractive as a route to optimum fuel economy.     

Comparison of myocontrol and force control based on fitts’ law model

In recent years, many types of input modalities have been developed and used for a great variety of new devices and machines. To enhance the performance of the human-machine systems, well-designed human-machine interface (HMI’s) between the user and the machine are essential. Biosignal-based HMI’s have been appearing as an alternative to physical HMI’s that have been conventionally used. As a type of biosignal control, the electromyography (EMG) has been investigated as an input modality for prostheses, computers, and robotic exoskeletons. In this study, myocontrol is analyzed through direct and numerical comparison with force control. Mycontrol and force control of visual pointing tasks were tested with EMG and force signals provided as visual feedback, and the controllability of each control mode was evaluated based on Fitts’ law paradigm, which is a general estimation method of speed and accuracy of various movements. The experimental results show that both myocontrol and force control can be modeled using Fitts’ law, even when different types of signals were provided as visual feedback. Among the control modes, myocontrol and force control showed high controllability when force signal was used as visual feedback.     

Online parameter identification of the asymmetrical Bouc–Wen model for piezoelectric actuators

The hysteresis of piezoelectric actuators (PAs) possesses the asymmetrical and frequency-dependent characteristics. In order to accurately model the hysteresis of a PA, an asymmetrical Bouc–Wen model is proposed and established in this paper. The recursive least-squares online identification method is used to real-time identify the parameters of the proposed model. Meanwhile, in order to avoid the data saturation phenomenon, the limited memory method is used to limit the number of the data sets. The experimental system is setup and the performance of this method is experimentally verified. Experimental results show that the proposed online identification method can effectively improve the modeling accuracy.     

A micro-contact and wear model for chemical–mechanical polishing of silicon wafers

A micro-contact and wear model for chemical–mechanical polishing (CMP) of silicon wafers is presented in this paper. The model is developed on the basis of elastic–plastic micro-contact mechanics and abrasive wear theory. The synergetic effects of mechanical and chemical actions are formulated into the model. A close-form equation of material removal rate from the wafer surface is derived relating to the material, geometric, chemical and operating parameters in a CMP process. The model is evaluated by comparing the theoretical removal rates with those experimentally determined. Good agreement is obtained for both chemically active and inactive polishing processes. The model reveals some insights into the micro-contact and wear mechanisms of the CMP process. It suggests that the removal rate is sensitive to the particle concentration in the slurry, more sensitive to the applied load and operating speed and most sensitive to the surface hardness and slurry particle size. The model may be used to study the effects of different materials, geometry, slurry chemistry and operating conditions on CMP processes.     

Experimental model and analytic solution for real-time observation of vehicle’s additional steer angle

The current research of real-time observation for vehicle roll steer angle and compliance steer angle（both of them comprehensively referred as the additional steer angle in this paper） mainly employs the linear vehicle dynamic model, in which only the lateral acceleration of vehicle body is considered. The observation accuracy resorting to this method cannot meet the requirements of vehicle real-time stability control, especially under extreme driving conditions. The paper explores the solution resorting to experimental method. Firstly, a multi-body dynamic model of a passenger car is built based on the ADAMS/Car software, whose dynamic accuracy is verified by the same vehicle＇s roadway test data of steady static circular test. Based on this simulation platform, several influencing factors of additional steer angle under different driving conditions are quantitatively analyzed. Then ε-SVR algorithm is employed to build the additional steer angle prediction model, whose input vectors mainly include the sensor information of standard electronic stability control system（ESC）. The method of typical slalom tests and FMVSS 126 tests are adopted to make simulation, train model and test model＇s generalization performance. The test result shows that the influence of lateral acceleration on additional steer angle is maximal （the magnitude up to 1°）, followed by the longitudinal acceleration-deceleration and the road wave amplitude （the magnitude up to 0.3°）. Moreover, both the prediction accuracy and the calculation real-time of the model can meet the control requirements of ESC This research expands the accurate observation methods of the additional steer angle under extreme driving conditions.     

Use of a higher order Heydemann–Welch model to characterize a controlled clearance piston gauge

We present a new method for characterizing a controlled-clearance piston gauge as a primary pressure standard. This method requires operating the piston gauge to jacket pressures of over 80% of the system pressure. We present measurements on a hydraulic piston gauge with a 290 MPa maximum pressure and a nominal piston diameter of 3.27 mm. Measurements showed that the cylinder becomes stiffer as the jacket pressure increases, and that non-linear models of the Heydemann–Welch parameters improve the determination of the effective area. The relative standard uncertainty in the effective area of the piston gauge ranges from 16.0 × 10⁻⁶ to 17.6 × 10⁻⁶, and the agreement to the present NIST pressure scale is within the standard uncertainty.     

Balancing–sequencing procedure for a mixed model assembly system in case of finite buffer capacity

In the last decades, the necessity to make production more versatile and flexible has forced assembly line production systems to change from fixed assembly lines to mixed model assembly lines, where the output products are variations of the same base product and only differ in specific customizable attributes. Such assembly lines allow reduced setup time, since products can be jointly manufactured in intermixed sequences (Boysen, Flieder, Scholl. Jena Research Papers in Business and Economics, Friedrich-Schiller-Universitat Jena, 1;1–11, 2007a; Boysen, Flieder, Scholl. Jena Research Papers in Business and Economics, Friedrich-Schiller-Universitat Jena, 2;1–33, 2007b). Unfortunately, the installation of customization options typically leads to variations in process times, and when the cycle is exceeded within a certain station, an overload is created, forcing other stations to wait and idle. Normally, process time variation in an un-paced line are absorbed by buffers, but in some industrial application the buffer dimensions are critical not only for the reduction of work in progress but also in reducing other constrains (space, technology, model dimensions, etc.). The problem of balancing mixed model assembly lines (MALBP), in the long term, and that of sequencing mixed model assembly lines (MMS), in the short term (Merengo, Nava, Pozetti. Int J Prod Res 37:2835–2860, 1999), are the two major problems to solve. The object of this paper is to illustrate an innovative balancing–sequencing step-by-step procedure that aims to optimize the assembly line performance and at the same time contain the buffer dimensions in function of different market demand and production mix. The model is validated using a simulation software and an industrial application is presented.     

Development of a radiative transfer model for the determination of toxic gases by Fourier transform–infrared spectroscopy with a support vector machine algorithm

Abstract

This report describes a radiative transfer model for Fourier transform-infrared (FT-IR) spectroscopy to create close-to-reality toxic gas spectra by reflecting the unique spectral responses of detectors and using the atmospheric radiative transfer code, MODTRAN. This system can be highly useful in overcoming the limitations for measuring toxic gases in open environments. The emulated gas spectra can be used to train support vector machine (SVM) for chemical gas detection. Its detection performance is evaluated with nerve agents (tabun, sarin, soman, and cyclosarin) and a simulant gas (sulfur hexafluoride) for indoor and outdoor experiments by using two off-the-shelf FT-IR gas detectors. The experimental results show that the proposed SVM algorithm successfully detected and classified targeted gases while reducing false negative and false positive detection rates.     

Bayesian regularization-based Levenberg–Marquardt neural model combined with BFOA for improving surface finish of FDM processed part

Fused deposition modeling has a complex part building mechanism making it difficult to obtain reasonably good functional relationship between responses and process parameters. To solve this problem, present study proposes use of artificial neural network (ANN) model to determine the relationship between five input parameters such as layer thickness, orientation, raster angle, raster width, and air gap with three output responses viz., roughness in top, bottom, and side surface of the built part. Bayesian regularization is adopted for selection of optimum network architecture because of its ability to fix number of network parameters irrespective of network size. ANN model is trained using Levenberg–Marquardt algorithm, and the resulting network has good generalization capability that eliminates the chance of over fitting. Finally, bacterial foraging optimization algorithm which attempts to model the individual and group behavior of Escherichia coli bacteria as a distributed optimization process is used to suggest theoretical combination of parameter settings to improve overall roughness of part. This paper also investigates use of chaotic time series sequence known as logistic function and demonstrates its superiority in terms of convergence and solution quality.     

Cost model development using virtual manufacturing and data mining: part II—comparison of data mining algorithms

Cost models of manufacturing processes are an important tool enabling enterprises to make reasonable predictions and forecasts in relation to the production costs for existing and new products. Accurate and robust cost models can help to provide significant competitive advantage for manufacturing organisations. Advanced computational methods such as virtual manufacturing and data mining have been identified as potentially powerful techniques for generating cost models that bypass the problems associated with traditional cost modelling processes. Part I, of this two-part paper, described the development of a cost model development methodology that makes use of virtual manufacturing models and data mining techniques and used case study data to validate this methodology. A critical part of this methodology is the selection and use of effective data analysis techniques that can identify accurate and robust cost estimating relationships. Part II now examines in detail the effectiveness of alternative data mining algorithms in terms of their ability to develop relationships that are (1) representative of the real causal relationships that exist and (2) able to provide a high level of estimating accuracy. More specifically, it focuses on the data generated by virtual manufacturing models and how the size and complexity of the generated data sets impact the accuracy of the cost estimating relationships.     

A new mathematical model for predicting the diameter expansion of flat ring in radial–axial ring rolling

An accurate prediction for the diameter expansion is quite essential for the ring rolling with large diameter since it determines the compatibility between the work rolls and the deformed ring in kinematics, so that the rolling stability and the final forming quality of the ring are influenced. A new mathematical model for predicting the diameter expansion of the flat ring in the radial–axial rolling process has been proposed, in which the variation of cross section, the particularity of initial rolling phase, and the effect of slip are all taken into consideration. Based on the proposed mathematical model, a 3D-FEM model for the radial–axial ring rolling process has been developed, and the corresponding experimentation has also been carried out. The diameter expansion in the simulation shows a good agreement with that in the experimentation. The forming quality comparison concerning the circularity, coaxiality, and tilting of the rolled ring has been executed between the former and new proposed method. The result indicates that the new mathematical method is very helpful to control the forming stability and hence improve the ring rolling quality significantly.     

Formation of a 1.3-MV voltage pulse across a 13-Ω load with the help of the model BMΓ-160 magnetocumulative generator

An energy source designed on the basis of a BMΓ-160 magnetocumulative generator with transformer output, which enables one to form high-power (>100 GW) pulses with a current rise time of ∼1 μs across a 10-Ω load is described. Test results are provided for the generator with a load in the form of a liquid resistor connected to the source through two series gas-filled discharge switches with a trigger level of 300–350 kV each. A voltage pulse of 1.3 MV was obtained across a resistive load of 13 Ω by means of electric explosion of the conductors. Experimental pulse parameters correspond to theoretical data. Numerical simulation indicates that voltage pulses with magnitudes >1 MV and a rise time of ∼100 ns can be formed across a resistance of 13 Ω.     

Finite element simulation of high-speed machining of titanium alloy (Ti�C6Al�C4V) based on ductile failure model

A Johnson?CCook material model with an energy-based ductile failure criterion is developed in titanium alloy (Ti?C6Al?C4V) high-speed machining finite element analysis (FEA). Furthermore, a simulation procedure is proposed to simulate different high-speed cutting processes with the same failure parameter (i.e., density of failure energy). With this finite element (FE) model, a series of FEAs for titanium alloy in extremely high-speed machining (HSM) is carried out to compare with experimental results, including chip morphology and cutting force. In addition, the chip morphology and cutting force variation trends under different cutting conditions are also analyzed. Using this FE model, the ductile failure parameter is modified for one time, afterword, the same failure parameter is applied to other conditions with a key modification. The predicted chip morphologies and cutting forces show good agreement with experimental results, proving that this ductile failure criterion is appropriate for titanium alloy in extremely HSM. Moreover, a series of relatively low cutting speed experiments (within the range of HSM) were carried out to further validate the FE model. The predicted chip morphology and cutting forces agree well with the experimental results. Moreover, the plastic flow trend along an adiabatic shear band is also analyzed.     

Modeling of transport phenomena and solidification cracking in laser spot bead-on-plate welding of AA6063-T6 alloy. Part I—the mathematical model

In this work, the oscillating arc narrow gap all-position gas metal arc (GMA) welding process was developed to improve efficiency and quality in the welding of thick-walled pipes. The statistical models of narrow gap all-position GMA weld bead geometry were developed using response surface methodology (RSM) based on central composite design (CCD). The developed models were checked for their adequacy and significance by ANOVA, and the effects of wire feed rate, travel speed, dwell time, oscillating amplitude and welding position on weld bead dimension were studied. Finally, the optimal welding parameters at welding positions of 0° to 180° were obtained by numerical optimization using RSM.