International Journal of Engineering
Volume:34 Issue: 11, Nov 2021

A novel Halbach permanent magnet array with rectangle section and trapezoid section is proposed and optimized in this paper. The analytical model of the premanent magnet segment is established based on the surface current method, which is numerically efficient and can be utilized to evaluate the magnetic field closely with the premanent magnet segment’s configurations. The analytical model of the Halbach array is acquired based on the superposition principle and coordinate transformation. The fundamental component of the magnetic flux density and the sinusoidal distortion rate are chosen as the optimization object. And the optimization is executed on the Halbach array with one specific set of dimensions by the genetic algorithm in global scale. The effectiveness of the optimization is validated by the finite element analysis. Compared to the traditional Halbach array with rectangle section, the magnetic field created by the optimized proposed Halbach array in this paper owns better performance.

This work proposes a geometrically non-linear vibratory study of a functional gradation beam reinforced by surface-bonded piezoelectric fibers located on an arbitrary number of supports and subjected to excitation forces and thermoelectric changes. The non-linear formula is based on Hamilton's principle combined with spectral analysis and developed using Euler-Bernoulli's beam theory. In the case of a non-linear forced response, numerical results of a wide range of amplitudes are given based on the approximate multimodal method close to the predominant mode. In order to test the methods implemented in this study, examples are given and the results are very consistent with those of the literature. It should also be noted that the thermal charge, the electrical charge, the volume fraction of the structure, the thermal properties of the material, the harmonic force and the number of supports have a great influence on the forced non-linear dynamic response of the piezoelectrically functionally graded structure.

One of the most important quality characteristics in a production process is the product lifetime. The production of highly reliable products is a concern of manufacturers. Since it is time-consuming and costly to measure lifetime data, designing a control chart seems difficult. To solve the problem, lifetime tests are employed. In the present study, one-sided and two-sided EWMA control charts are designed under a type II censoring (failure censoring) life test. Product lifetime is a quality characteristic dealt with in this study. It is assumed to follow the Weibull distribution with a fixed shape parameter and a variable scale parameter. In order to design a control chart, first, the control chart limits are calculated for different parameters, and then the Average Run Length (ARL) in the out-of-control state is used to evaluate the performance of the proposed control chart. Next, a comprehensive sensitivity analysis is performed for the different parameters involved. The computational results show that the one-sided control chart has better performance to detect the shift of lifetime data than the two-sided control chart. The average run length curve of the two-sided control chart is biased, while that of the one-sided control chart is unbiased. A very effective parameter that increases the performance of a control chart is found to be the number of failures in the failure censoring process. Finally, simulated and real examples are provided to show the performance of the proposed control chart.

In this paper, a new method is introduced to synthesize the original data obtained from simulation or measurement results in the form of a rational function. The integration of the available data is vital to the performance of the proposed method. The values of poles and residues of the rational model are determined by solving the system of linear equations using the conventional Least Square Method (LSM). To ensure the stability condition of the provided model, a controller coefficient is considered. Also, using this parameter, the designer can increase the stability margin of a system with poor stability conditions. The introduced method has the potential to be used for a wide range of practical applications since there is no specific restriction on the use of this method. The only requirement that should be considered is the Dirichlet condition for the original data, usually the case for physical systems. To verify the performances of the proposed method, several application test cases are investigated and the obtained results are compared with those gathered by the well-known vector fitting algorithm. Also, the examinations show that the method is efficient in the presence of noisy data.

Mode I fracture toughness of carbon/ glass reinforced polyster hybrid composite was invesitigated expermrntally and numerically by using the cosmos)/m 2.6 finite element software (fms) by utulizing the hand laup techniqe)(HLU). The single edge notch bending (SENB) test was developed to evalute the mode l fracture toughness of carbon composites, glass composite and hybrid compodite materials at varuos fiber configurations. Scaning electron microscope (SEM) was used to examine the fracture surface of the hybrid composite material under the effect of mode l loading. the expermental result showed the maximum stress intensity (sif) factor 882mpa. mm1/2. obtained in the hybrid composite with stacking dequencess (c/g/g/c) during the mode l loading compared to other stacking sequences. this is attributed to the goid interfical between the carbon and glass fibers and matrix face. From the resukts, it was suggested that the expermental results is a goid a gremnent with the finite element modelling

Carbon Nanotube Field Effect Transistors (CNFET) are considered to be the potential candidates for overcoming the shortcomings associated with the scale of the art CMOS transistors; as the scaling continues. In this paper a digitally reconfigurable CNFET based biquadratic multifunctional filter employing a CNFET based single Differential Voltage Current Conveyor (DVCC) at 32nm technology node has been presented. The circuit utilizes a single CNFET based DVCC block along with the arrangement of few resistors and capacitors. The proposed digitally reconfigurable multifunctional filter circuit is able to obtain programmable low pass, high pass and band pass filter configurations using the same topology. The designed CNFET based multifunctional filter obtains a resonant frequency of the order of GHz. Furthermore, a 3-bit digital control of the designed multifunctional filter parameters i.e. Quality Factor (Qo) & resonant frequency has been made possible using the Current Summing Network (CSN). Sensitivity and comparative analysis has also been performed. The circuit has been simulated at a low voltage supply of 0.9V using HSPICE environment at 32nm technology node. The simulation results obtained are in sync with the theoretical analysis.

In this paper, the authors present a novel approach to design a high-speed permanent magnet synchronous generator (HS-PMSG) with a retention sleeve. The importance of the retention sleeve becomes conspicuous when the rotor suffers from the radial and tangential stresses derived from a high speed say 60 krpm. With respect to the mechanical property of Titanium, this material has been demonstrated that it could be a proper material for the retention sleeve. The investigations of this paper are concentrated on the electromagnetic coupled with mechanical design of a 2-poles, 18-slots, 40 KW HS-PMSG which is carried out through FEM analysis using JMAG 17.1 and ABAQUS CAE and optimized through the well-known Taguchi optimization method. The obtained results assure the robust mechanical behaviour of the HS-PMSG at a rotational speed of about 60 krpm meanwhile the cogging torque, the Joule loss, and the total weight of the optimally designed HS-PMSG are reduced 44.71%, 27.87%, and 2.78%, respectively compared with the initial design.

Due to the limited space in transport vehicles, the CI engines with high power density has always been a priority. In heavy-duty diesel engines, direct injection results creation of the lean region in the space of the combustion chamber. Increasing the fuel penetration by changing injection duration is an effective solution to achieve homogenous mixture. In this paper, impact of changing Injection duration in upgraded MTU-4000-R43L diesel engine on power characteristics, rate of heat release (RoHR), combustion phasing, emission and, most importantly, the gradient of pressure changes as a characteristic of the vibration and knocking of the engine, has been studied numerically. Numerical simulation is performed in AVL Fire which is coupled with reduced detail chemical kinetics. the fuel Injection duration was varying from 14.6 to 35.6 oCA, the in-cylinder mean pressure, the IMEP decreases and the ISFC increases; however as the fuel Injection duration decreases, the pressure gradient rises; from the range of 30.6 degrees onwards, the reduction of the fuel Injection duration leads to a severe knock of the engine and as a result reduces its engine life. Emission results also showed that CO2 and NOx increased and CO reduced with decreasing fuel decreasing Injection duration.

The important thing about axially loading slim columns is buckling stability. However, very limited researches were found, especially using glass-reinforced concrete. An ASR (alkali silica reaction) deterioration problem only occurs when particles are very fine. The utilization of glass as a particle was avoided, and bigger dimension of glass strip waste was utilized instead because cement cannot penetrate deep into the glass piece. A series of axial loading tests of GLARC (glass-reinforced concrete) slim columns were carried out on arrangement types; glass strips, homogenous and randomly pieces reinforced to explore their buckling performance. All axial GLARC columns capacity results better than glassless columns reinforcement. The best reinforcement was longitudinal horizontal strip arrangement since they have consistent strength contribution hence allow the GLARC columns to resist higher axial loads to avoid buckling failures. The tests results in a good performance and hence GLARC columns have potential chances to be used extensively as structural compression members.

In the recent decade, very few studies have been done on mine reclamation cost estimation and no study has been conducted on proposing mine reclamation cost estimation models based on historical data. This study aims to develop predictor models for mine reclamation costs. To this end, after collecting the historical cost data of 41 open-pit mine reclamation projects, a comprehensive data set of 16 mine reclamation costs groups and the extent of the disturbed mined land corresponding to each group was prepared. Given the advantage of the regression method in developing a reliable predictor model with few data, the proposed cost models are developed based on the regression analysis technique. The R square for all and more than 87% of the developed models was more significant than 85% and 90%, respectively, indicating the proper fits on the data sets. Also, the root mean square error ratio to the standard deviation of observed cost data (RSR) was lower than 0.7 for all developed models, indicating the predictor models' good performance on reliably estimating mine reclamation costs. These efficient and simple general models can help make the right decisions by mine reclamation planners and pave the way to achieve sustainable mining by considering mine reclamation cost in the mine planning and design process.

In this study, the fragility curves were developed for three-, five-, and eight-story moment resisting steel frame structures with considering soft story and torsional irregularities during the earthquake mainshock to assess the probabilistic effects of irregularities in plan and height of steel structures. These models were designed according to Iranian seismic codes. 3D analytical models of steel structures were created in the OpenSees software platform and Incremental Dynamic Analysis (IDA) was conducted to plot the IDA curves. The maximum value of inter-story drift was selected as the demand parameter and the capacity is determined according to the HAZUS-MH limit states; and finally, the corresponding fragility curves were developed. The results of the 3D nonlinear dynamic analysis indicated that the damage state of the structure due to soft story irregularity was decreased with increasing stories. On the other hand, the damage caused by torsional irregularity in plan was increased by increasing the height of the structure. For example, in the 3-story structure, soft-story effect on damage probability was more dominant than torsional irregularity.

Nowadays, data mining has become significant given the popularity of social networks as well as the emergence of abbreviated words, foreign terms and emoticons in the Persian language. Meanwhile, numerous studies have been conducted to identify the type of words. On the one hand, identifying the role of each word in a sentence is far more important than identifying the type of word in the sentence. On the other hand, the spelling-grammatical similarity of Persian to Arabic has enabled the newly proposed method in this paper to be applied to Arabic. In this paper, we adopted the Hidden Markov Model (MHM) and Tri-gram tagging with the aim of identifying the morphology of composition roles in Persian sentences. Then, a comparison was made between the technique developed in this paper and the Hidden Markov Model, Uni-gram and Bi-gram tagging. The proposed method supports the results obtained by the word role identification through "independent" and "dependent" roles and several factors that have a contribution to the words roles in sentences. In fact, the simulation results show that the average success rates of independent composition roles with MHM and Tri-gram tagging were 20.56% and 17.67% compared to Uni-gram and Bi-gram methods, respectively. Regarding the dependent composition role, there were improvements by 24.67% and 32.62%, respectively.

Machine maintenance is performed in production to prevent machine failure in order to maintain production efficiency and reduce failure costs. Due to the importance of maintenance in production, it is necessary to consider an integrated schedule for production and maintenance. Most of the literature on machine scheduling assumes that machines are always available. However, this assumption is unrealistic in many industrial applications. Preventive maintenance (PM) is often performed in a production system to prevent premature machine failure in order to maintain production efficiency. However, this assumption is inappropriate in real industrial cases. Machine maintenance plan is often performed in a production system to prevent premature machine failure in order to maintain production efficiency. Parallel machine layout is very common in modern production systems. Its performance sometime has a key impact on overall productivity. In this paper, a parallel machine scheduling problem with individual maintenance operations is considered. Then, a mathematical model is formulated including scheduling and maintenance operation optimization. The objective is to assign all jobs to machines so that the completion time and the average cost are minimized, jointly. Maintenance is considered in time intervals. To solve the proposed problem, a branch and bound (B&B) algorithm is adapted and proposed. The results show the applicability of the mathematical model in production systems and efficiency of the adapted B&B in comparison with Gams optimization software.

The brake pad plays a crucial role in the control of vehicle and machinery equipment and subsequent safety. There is always a need for a new functional material with improved properties than existing ones. The present research study was carried out to develop a new brake pad material made up of polymer nanocomposite for enhanced physical, mechanical, and frictional characteristics in comparison to existing brake pad materials. In this study, polymer nanocomposite samples were developed and their physical properties namely density, water-oil absorption, and porosity were evaluated. Mechanical hardness of developed samples was estimated with Vicker’s hardness tester. Frictional characteristics of samples and wear values determined with pin or disc apparatus. Dry sliding behavior was examined by conducting multiple trials with sliding speed in the span of 2-10 m/s and load were changed from 20 N to 100 N to discuss the effect of velocity, the effect of nominal contact pressure and the effect of sliding distance on friction and temperature parameters. Morphology of prepared brake pad samples was characterized with the Scanning electron microscope. Scanning electron micrographs of brake pad surfaces showed different shape wear debris and plateaus significantly affecting the friction characteristics. Developed samples along with commercial specimens show excellent resistance to water and oil absorption. Thus obtained results for evaluated polymer nanocomposite brake pad samples demonstrate their potential for brake pad applications.

Geopolymer is of the promising eco-friendly materials that can be produced with variety of physical and mechanical properties through alerting the processing parameters. Obtaining Geopolymer with high compressive strength and high porosity may make this material as a preferred candidate for many thermal and physiochemical applications. This research aims to identify the set of the processing parameters that yield such as these Geopolymer materials. Taguchi method combined with Grey relational analysis has been used to solve this multi response trouble. The analysis and the experimental results showed that it is possible to achieve this aim by using low amount of hydrogen peroxide as foaming agent, low amount of yeast as catalyst, and low amount of vegetable oil as a stabilizer. Furthermore, the polymerization time elapse before adding the foaming agent is found to be important processing parameter. Also, the experimental results showed that high porosity and adequate compressive strength can be obtained at the same geopolymer body by choosing the suitable values of the processing parameters. Moreover, it has been found that the use of yeast as catalyst and the polymerization time are important processing parameters. Also, it has been noticed that the amount of the vegetable oil, which is used as stabilizer, should be kept in low values to obtain the optimal compressive strength and porosity.

This paper presents a new MEMS variable capacitor to achieve high stable region and extremely wide tunability. The idea is based on increasing the stable region in the gap between the plates of the capacitor. It is done by combining the functionality of two different vertical comb drive actuator sets to takeover a unity air gap variation. The design of the structure is carried out so that the performance of these two actuator sets is fully independent of one another and without any destructive or damaging effect on each other. The advantage of this scheme is that adding the second mechanism of actuation does not change the overall structure thickness compared with when the structure uses a single actuation mechanism. Therefore, the tunability increases sharply. Aluminum is the structural material used for the designs. Comb actuators are widely used as MEMS motors due to their long range of linear motion, low power consumption and ease of fabrication. A full review of electrostatic actuator portion is done. The structure is calculated using MATLAB software. To verify, the calculated results are compared with simulated results using Intellisuite software. The natural frequency is 1.173 KHz. According to calculation and simulation results the achieved minimum tuning range is 2300%.

Interval data are usually applied where inaccuracy and variability must be considered. This paper presents a learning method for Interval Extreme Learning Machine (IELM) in classification. IELM has two steps similar to well known ELM. At first weights connecting the input and the hidden layers are generated randomly and in the second step, ELM uses the Moore–Penrose generalized inverse to determine the weights connecting the hidden and output layers. In order to use Moore–Penrose generalized inverse for determining second layer weights in IELM, this paper proposes four classification methods to handle symbolic interval data based on ELM. The first one uses a midpoint of intervals for each feature value then it applies a classic ELM. The second one considers each feature value as a pair of quantitative features and implements a conjoint for classic extreme learning machine. The third one represents interval features by their vertices and performs a classic extreme learning machine as well. The fourth one takes each interval as a pair of quantitative features after that two separated classic extreme learning machines are performed on these features and combines the results accordingly. Algorithms are tested on the synthetic and real datasets. A synthetic dataset is applied to determine the number of hidden layer nodes in an IELM. The classification error rate is considered as a comparison criterion. The error rate obtained for each proposed methods is 19.1667%, 15% , 6.5358% and 18.3333% respectively. Experiments demonstrate the usefulness of these classifiers to classify symbolic interval data.

Most of the existing codes are using stress block parameters which were derived for normal strength concrete. Rectangular stress-block parameters used for normal strength concrete cannot be used safely for higher grade concrete like HPC, hence new stress-block parameters are established from the experimental investigations. Theses parameters can be made very much useful in the design of HPC members. Present research aims at behaviour study of HPC using stress block parameters. High performance concrete single span beams were tested under monotonic four-point bending. Considering the experimental stress-strain curves of HPC for grade 60, 80 and 100 MPa, an idealized stress block curve is established and the stress block parameters are derived. Based on the idealized stress block curve, the equations for ultimate moment of resistance, depth of neutral axis, limiting moment of resistance and maximum depth of neutral axis are proposed. Based on the observation of experimental load deformation curves, an ideal load deformation curve is proposed, which follows four significant events identified as, first cracking, yielding of reinforced steel, crushing of concrete with spalling of cover and ultimate failure. The predicted values compare well with the experimental values. The average location of the first crack observed was at 0.535 times the span of the beam from the left support of the observer in the tension zone.