A current–voltage–temperature method for fast extraction of schottky diode static parameters

We propose a simple graphical method to extract the static parameters of an arbitrary schottky diode. The method is an extension of the current–voltage method by the inclusion of a temperature aspect, and hence may be referred to as a current–voltage–temperature (I–V–T) method. The voltage–temperature characteristics are first obtained at two constant currents. Then, by considering the points on the characteristics with common attributes of either voltage or temperature under specified current density, a specific parameter is calculated. This abstraction is shown mathematically to greatly simplify the calculation of ideality factor, barrier height and diode resistance. The diode is first considered to be ideal with zero current modulation by a base resistance. The effect of non-zero base resistance is then subsequently quantified. Finally, the analysis of simulations on the commercial BAT54 schottky diode and published data for fabricated Au/n-Ge, Au/n-Si and Au/n-GaAs schottky diodes are presented. Application of the I–V–T method to different regions of the characteristics produces much lower variances in calculated barrier height, ideality factor and forward resistance in contrast to those based on the source publications. This suggests that the I–V–T method is a feasible alternative to characterize these diodes. The underlying reason being that control is exerted on the current density by the experimenter.     

Further Development of Oxley’s Predictive Force Model for Orthogonal Cutting

An analytical modelling approach based on Oxley's predictive machining theory is presented to evaluate the cutting forces, chip thickness and temperature distributions in the orthogonal cutting process. In this approach, the work material properties are modelled using the Johnson–Cook constitutive material law, which represents the flow stress of the material as a function of strain, strain rate, and temperature. For the determination of the tool-chip interface temperature, an evenly distributed rectangular heat source near the cutting edge is used instead of a plane heat source. The tool thermal model is simplified by neglecting the temperature variations along the tool-chip interface to avoid the high cost of computation time. Finite difference method is applied for solution of the thermal model. The performance of the developed model is validated with the experimental data in machining of steel 1045. A comparison of the outputs from Oxley's original model and the modified model is provided. The model is further assessed by using two other materials, Al 6086-T6 and Ti6Al4V. Close agreements with experimental results have been shown.     

Model Based Tuning of Controller for Non‐Linear Hemispherical Tank Processes

Abstract

A non linear liquid level process represented by a 5 liter hemispherical tank was subjected to dynamic analysis using a step response technique. The data fitted a first order plus dead time model with an error of less than 3 percent. The level was measured using an on‐line Honeywell capacitance sensor. From the model parameters, PI and fuzzy tuned PI controllers were designed using MATLAB. The closed loop performance was studied for both the servo and regulator problems. Based on the overshoot, rise time, settling time, and ISE, it is found that the Fuzzy tuned PI controller is better suited for this process.     

A Model for the Assessment of Wheel–Rail Contact in the Presence of Solid Contaminants

An analytical model for the assessment of a contact in the presence of a solid contaminant is presented, mainly aimed at studying the damage to railway wheels and rails operating in third-body-contaminated environments. The model, developed under 2D plane strain idealization, includes multiple evenly spaced rigid cylindrical contaminant bodies entrapped between two elastic cylinders. It allows a very fast calculation of the pressure distribution on the surfaces in contact and it can be used for evaluating the stress field in the subsurface region, at both the small scale of the contact between the main body and the contaminant body and the full scale of the contact between the two main bodies. The model was validated by comparison with finite element (FE) analyses, showing its accuracy. Some examples of application showed the model’s ability to predict the limit of the influence of the solid contaminant bodies and the depth where cyclic plasticity phenomena occur in wheel–rail contacts.     

Application of Hilbert–Huang Transform to acoustic emission signal for burn feature extraction in surface grinding process

This paper presents a sensor system using motor current sensors, voltage sensors, accelerator and acoustic emission sensor for grinding burn feature extraction. The new method, Hilbert–Huang transform (HHT), was applied as a signal processing tool to digest the raw acoustic emission and accelerator signals and to extract grinding burn features. A filtering criterion using average energy percentage of IMF components was proposed in order to simplify the calculation. Five IMF components were selected based on this criterion and their marginal spectra were calculated. The marginal spectral amplitude of the first three IMF components and the spectral centroid of the last two IMF components clearly reflected the occurrence of grinding burn. Results indicate that the application of HHT to acoustic emission signals in grinding burn detection is of great potential. Besides, the wheel rotation speed can be successfully uncovered through the intrinsic mode function (IMF), which verified the physical meaning of the EMD method.     

2D Model of Guide Vane for Low Head Hydraulic Turbine： Analytical and Numerical Solution of Inverse Problem

Low-head hydraulic turbines are the subjects to individual approach of design. This comes from the fact that hydrological conditions are not of a standard character. Therefore, the design method of the hydraulic turbine stage has a great importance for those who may be interested in such an investment. As a first task in a design procedure the guide vane is considered. The proposed method is based on the solution of the inverse problem within the flame of 2D model. By the inverse problem authors mean a design of the blade shapes for given flow conditions. In the paper analytical solution for the simple cylindrical shape of a guide vane is presented. For the more realistic cases numerical solutions according to the axis-symmetrical model of the flow are also presented. The influence of such parameters as the inclination of trailing edge, the blockage factor due to blade thickness, the influence of loss due to dissipation are shown for the chosen simple geometrical example.     

Evaluation of performance of nanofluid using multiwalled carbon nanotubes for machining of Ti–6AL–4V

Machining of titanium alloys generate very high temperature in the cutting zone. This results in rapid tool wear and poor surface properties. Therefore, improvement in cutting performance in machining of titanium alloys is very much dependent on effectiveness of the cooling strategies applied. In the present work, performance of nanofluid using multiwalled carbon nanotubes (MWCNTs) dispersed in distilled water and sodium dodecyl sulfate (SDS) as surfactant is evaluated for turning operation on Ti–6Al–4V workpieces. Turning operations were carried out under three different conditions – dry, with conventional cutting fluid and with nanofluid. Nanofluid application was limited to 1 L/h and it was applied at the tool tip through gravity feed. Various machining responses like cutting force, surface finish and tool wear were analyzed while turning at optimum cutting parameters as 150 m/min, 0.1 mm/rev and 1 mm depth of cut. Later on, machining performance of nanofluid is confirmed at low cutting speed of 90 m/min. Nanofluid outperformed conventional cutting fluid with 34% reduction in tool wear, average 28% drop in cutting forces and 7% decrease in surface roughness at cutting speed of 150 m/min.     

Development of a system for monitoring tool condition using acousto-optic emission signal in face turning—an experimental approach

In automated manufacturing systems, one of the most important issues is accurate detection of the tool conditions under given cutting conditions so that worn tools can be identified and replaced in time. In metal cutting as a result of the cutting motion, the surface of workpiece will be influenced by cutting parameters, cutting force, and vibrations, etc. But the effects of vibrations have been paid less attention. In the present paper, an investigation is presented of a tool condition monitoring system, which consists of a fast Fourier transform preprocessor for generating features from an online acousto-optic emission (AOE) signals to develop a database for appropriate decisions. A fast Fourier transform (FFT) can decompose AOE signals into different frequency bands in the time domain. Present work uses a laser Doppler vibrometer for online data acquisition and a high-speed FFT analyser used to process the AOE signals. The generation of the AOE signals directly in the cutting zone makes them very sensitive to changes in the cutting process due to vibrations. AOE techniques is a relatively recent entry into the field of tool condition monitoring. This method has also been widely used in the field of metal cutting to detect process changes like displacement due to vibration and tool wear, etc. In this research work the results obtained from the analysis of acousto-optic emission sensor employs to predict flank wear in turning of AISI 1040 steel of 150 BHN hardness using Carbide insert and HSS tools. The correlation between the tool wear and AOE parameters is analyzed using the experimental study conducted in 16 H.P. all geared lathe. The encouraging results of the work pave the way for the development of a real-time, low-cost, and reliable tool condition monitoring system. A high degree of correlation is established between the results of the AOE signal and experimental results in identification of tool wear state.     

Characteristics of a pulse–periodic CO<Subscript>2</Subscript> laser for applications in the field of laser-produced plasma

The design of a pulse–periodic СО₂ laser oscillator that operates at a high level of the specific energy deposition into a self-sustained discharge is described. The laser is intended for generating pulses with a high-density radiation flux in a laser-plasma generator of multiply charged ions at the Institute of Theoretical and Experimental Physics (ITEP). The results of investigations of the spatiotemporal and energy characteristics of laser output radiation in a wide range of the discharge excitation level and the mixture composition are presented. The optimal conditions are determined under which the oscillator provides an output energy of >10 J in a pulse with a duration of ~28 ns and a record specific peak radiation power of 190 MW per liter of the active volume of a CO₂: N₂: He mixture. The high quality of the spatial characteristics was confirmed in measurements of the radial energy-density distribution in the far-field zone, whose characteristic size is close to the diffraction limit.     

A calorimeter for detecting hadrons with energies of 10–100 GeV

A calorimeter for detecting hadrons in the energy range 10–100 GeV is described. It is used at CERN in the NA58 (COMPASS) experiment aimed at studying the nucleon structure and spectroscopy measurements of charmed particles. The calorimeter is composed of 480 modules with a cross section of 15×15 cm², assembled in a matrix with dimensions of 4.2×3 m² and a central window of area 1.2×0.6 m². In each module are 40 iron and scintillator layers of a total thickness of 4.8 interaction lengths. The energy resolution of the calorimeter for hadrons (pions) and electrons and the spatial resolution, determined on the test beams, are $\frac{{\sigma _\pi (E)}}{{E[GeV]}} = \frac{{59.4 \pm 2.9}}{{\sqrt E }} \oplus (7.6 \pm 0.4)\% ;\frac{{\sigma _e (E)}}{{E[GeV]}} = \frac{{24.6 \pm 0.7}}{{\sqrt E }} \oplus (0.7 \pm 0.4)\% $ , and σ _x,y ≈ 15 mm, respectively. The average value of the e/π ratio that characterizes the amplitude responses of the calorimeter to electrons and pions with equal energies from the above range is 1.2 ± 0.1. This study was performed at the JINR Laboratory for Particle Physics.     

Analysis of the influential pressures for green supply chain management adoption—an Indian perspective using interpretive structural modeling

Presently, industries face tremendous pressure from customer’s environmental awareness and stricter environmental regulations to incorporate ethical and environmental considerations in all facets of traditional supply chain management (TSCM). Green supply chain management (GSCM) is a well-known and established concept to incorporate ethical, environmental considerations in TSCM which satisfies the needs of environmental policies and customers and restricts hazards. The objective of this paper is to identify the key pressures of motivation for adoption of GSCM in TSCM. This paper, initially identified 25 pressures from previous literature sources, secondly influential pressure was determined with help of interpretive structural modeling technique through expert’s opinion. This technique identified five level of influential pressures from recommended 25 pressures based on the impact. The result of this paper inferred that Indian auto component manufacturing industries are facing pressure from government and regulation policies categories. The study result is helpful to visualize which pressure provides more motivation to GSCM practices and which pressure is motivation-less to engage GSCM in traditional activities, especially to maintain environmental regulation policies. This approach was conducted with 16 auto components manufacturing industries in Tamilnadu, South India.     

An efficient cardiac signal enhancement using time–frequency realization of leaky adaptive noise cancelers for remote health monitoring systems

Nowadays telecardiology is an important tool in cardiac diagnosis from a remote location. During Electrocardiogram (ECG) or Cardiac Signal acquisition several artifacts strongly affect the ST segment, degrade the signal quality, frequency resolution, produce large amplitude signals in ECG that can resemble PQRST waveforms and mask the tiny features that are important for clinical monitoring and diagnosis. So the extraction of high-resolution cardiac signals from recordings contaminated with artifacts is an important issue to investigate. In this paper, various novel block based time–frequency domain adaptive filter structures for cardiac signal enhancement are presented. These filters estimate the deterministic components of the cardiac signal and remove the noise component. The Block Leaky Least Mean Square (BLLMS) algorithm, being the solution of the steepest descent strategy for minimizing the mean squared error in a complete signal occurrence, is shown to be steady-state unbiased and with a lower variance than the LMS algorithm. To improve the filtering capability some variants of BLLMS, Block Normalized LLMS (BNLLMS) and Block Error Normalized LLMS (BENLLMS) algorithms are implemented in both time domain (TD) and frequency domains (FD). Finally, we have applied these algorithms on real cardiac signals obtained from the MIT-BIH data base and compared their performance with the conventional LLMS algorithm. The results show that the performance of the block based algorithms is superior to the LLMS counterparts in terms of signal to noise ratio improvement (SNRI), excess mean square error (EMSE) and misadjustment (M). Among all the algorithms FDBENLLMS achieves higher SNRI than other techniques. These values are 25.8713 dB, 20.1548 dB, 21.6718 dB and 20.7131 dBs for power line interference (PLI), baseline wander (BW), muscle artifacts (MA) and electrode motion artifacts (EM) removal.     

FPGA based chip emulation system for test development of analog and mixed signal circuits: A case study of DC–DC buck converter

Prototyping on FPGA has become a main stream verification methodology for hardware design, test development, software co-design, etc. in the area of digital VLSI. In the case of test development, FPGA serves as a virtual DUT (Design Under Test) and test patters are applied from automatic test equipment (ATE). This verifies not only the chip with design for test (DFT) circuitry and test program but also the entire test setup involving virtual DUT, load board, interconnections with ATE, etc. Although, FPGA based platform is used widely for test program verification of digital ICs, this technique is not used for analog/mixed signal (AMS) circuits because of the difficulty in implementing AMS circuits in FPGAs. This work is concerned with the development of a test emulation platform, termed as hand-in-hand test flow, of AMS circuits based on FPGA. The proposed methodology exploits fixed-point modeling and DSP implementation techniques facilitated by latest FPGAs to model the AMS circuits. The proposed hand-in-hand test flow for AMS circuits will help the test engineers to start their test plan concurrently with the design engineers and validate them much prior to the first silicon. We have illustrated the proposed scheme using the case study of a current programmed buck type switching converter on Xilinx® Virtex™-5 FPGA. The FPGA emulation measurement results show that performance of the emulated DC–DC buck converter (e.g., duty ratio test, line transient, load step) matches well with that of SPICE simulation.     

Optimal Neural Network Model for Characterization of Process‐Induced Damage in Drilling Carbon Fiber Reinforced Epoxy Composites

In this paper, a method for robust design of a neural network (NN) model for prediction of delamination (Da), damage width (Dw), and hole surface roughness (Ra) during drilling in carbon fiber reinforced epoxy (BMS 8‐256) is presented. This method is based on a parametric analysis of neural network models using a design of experiments approach. The effects of number of neurons (N), hidden layers (L), activation function (AF), and learning algorithm (LA) on the mean square error (MSE) of model prediction are quantified. Using the aforementioned method, a robust NN model was developed that predicted process‐induced damage with high accuracy.     

A Three-Dimensional Navier-Stokes-Based Numerical Model for Squeeze Film Dampers. Part 2—Effects of Gaseous Cavitation on the Behavior of the Squeeze Film Damper

The damping coefficients for a squeeze film damper (SFD) were determined and discussed in Part 1 using the full Navier-Stokes equations (NSE) coupled with a homogeneous cavitation model. In this continuation, Part 2, article these coefficients are introduced into the governing equations of motion to determine the trajectory of the rotor and its stability. The nonlinear response of the damper predicted by the NSE model is compared to results obtained from the application of the Reynolds equation. The influences of gas mass concentration as well as that of the amount of imbalance on transmissibility and eccentricity of the damper are also investigated.     

A Peltier cells differential calorimeter with kinetic correction for the measurement of cp(H,T) and Δs(H,T) of magnetocaloric materials

In this paper we describe and test a setup for the characterization of the magnetocaloric effect around room temperature. The setup is a differential calorimeter able to measure both the specific heat c(p)(H,T) under constant magnetic field H and the isothermal entropy change induced by changing H, Δs(H,T), in the room temperature range. The setup uses miniaturized Peltier cells to measure the heat flux, with resolution of about 1 μW, and power Peltier cells to regulate the temperature in the range from 243 K (-30 °C) to 343 K (+70 °C). The kinetic effects due to the heat capacity of the measuring cells are taken into account by a simple model of the heat flux diffusion in the calorimetric cell. As measurement examples, we show the characterization of the magnetocaloric effect in magnetic materials with a second order transition [without latent heat and without hysteresis, as in the La(1)(Fe(1-x-y)Co(y)Si(x))(13) alloy with x=0.077 and y=0.079] and with a first order transitions (with latent heat and hysteresis as in Ni(50)Mn(36)Co(1)Sn(13)). As a result we compare the entropy change Δs(H,T) derived from (i) the integration of the specific heat c(p)(H,T) and (ii) the direct isothermal measurements, obtaining an excellent agreement.     

Wear mechanisms analysis for turning Ti-6Al-4V—towards the development of suitable tool coatings

Titanium alloys are materials of choice for a wide range of applications. Their high strength and low density make them suitable for aerospace applications. Titanium-based alloys also exhibit excellent corrosion resistance and are bio-compatible, making them suitable for prosthetic applications like orthopedic transplants. The reactivity as well as heat resistance of titanium-based alloys, however, renders them difficult to machine. Based on previous research involving the development of a wear map for Ti-6Al-4V alloy, this research aims to identify the wear mechanisms associated with tool deterioration across different regions of the wear map. The characterization of wear mechanisms with respect to machining conditions and tool wear rate would ultimately help in the development of suitable tool coatings for machining titanium-based alloys.     

Study of the intrinsic mechanisms of nickel additive for grain refinement and strength enhancement of laser aided additively manufactured Ti–6Al–4V

It is well-known that grain refiners can tailor the microstructure and enhance the mechanical properties of titanium alloys fabricated by additive manufacturing(AM). However, the intrinsic mechanisms of Ni addition on AM-built Ti–6Al–4V alloy is not well established. This limits its industrial applications. This work systematically investigated the influence of Ni additive on Ti–6Al–4V alloy fabricated by laser aided additive manufacturing(LAAM). The results showed that Ni addition yields three ...