Advances in Engineering Research and Application

The paper presents a robust control approach to self-balancing bikes (SBB) against unknown system parameters and external disturbances. The system is mechanically balanced by the momentum force produced by a flywheel. Initially, sliding mode control is employed for balancing the bike in roll motion and steering. Based on the designed control, a high-gain observer is developed to estimate the bike roll inertia momentum which is difficult to derive in practice. The stability of the overall system including estimated inertia momentum is given. Comprehensive simulations are performed to demonstrate the proposed control.

In the machining of hard material, the cutting force has a direct impact on the lifetime of the cutting tool, the vibration of the system, and more importantly the quality of the machined surface. On the other hand, the cutting force can be easily observed by using a three-component dynamometer. The goal of this research was to minimize the cutting force during milling JIS SKD61 steel under minimum quantity lubrication (MQL) aided SiO2 nanoparticles. The resultant cutting force was determined by three components: the feed force (Fx), the thrust force (Fy), and the tangential force (Fz). Cutting speed, feed rate, and depth of cut together with the hardness of the work-piece were selected as input parameters. Experiments were carried out based on the G. Taguchi method with L27 orthogonal arrays was used to find the effects of input parameters on the resultant cutting force. Analysis of variance (ANOVA) showed that the depth of cut had the most influence on the cutting force.

The purpose of this paper is to compare the ride performance of a liquid-filled cab mount system (LCMs) with an annular orifice and an original rubber cab mount system (RCMs) under the operating conditions. In order to achieve these goals, a nonlinear dynamical model of LCM is set up to determine its vertical force which is connected with a half-vehicle ride dynamic model of a double-drum vibratory roller under two survey cases. The root-mean-square (RMS) and power spectral density (PSD) acceleration responses of the driver’s seat and pitching cab angle are chosen as the objective functions. The ride performance of LCMs is verified and compared with RCMs through objective functions. The study results show that the values of the root mean square (RMS) acceleration responses with LCMs are respectively reduced in comparison with RCMs and the peak amplitude values of PSD acceleration responses are respectively reduced when compared with REMs in low frequency region from 0.5Hz to 60Hz when both the vehicle and drums operate under two cases. The performance of LCMs is better than that of RCMs in improving the ride comfort of a double-drum vibratory roller under two survey cases.

This research presents different approaches of data analyzing and modelling to detect the milling status (i.e., milling/idling) based on the vibration of 3 axes. Data harvested during experiments, which represented in time domain, was transformed into frequency domain by Fast Fourier Transform (FFT) method in order to get more useful information and reduce noise. Neural network (NN) and Support Vector Machine (SVM) were two supervised machine learning and classification models which were used to train the data. The structure of the two models were selected by using Genetic Algorithm (GA) and Non-Dominated Sorting Genetic Algorithm – II (NSGA-II). A preferable recognition rate of 99.6% was achieved by Neural network with Genetic algorithm implemented.

NoSQL databases have recently become increasingly popular as data platforms for big data and real-time web applications. Due to the simplicity in design but effectiveness in horizontal scaling and performance, NoSQL databases can be a better alternative approach in comparison with traditional relational databases. However, the lack of a fine-grained access control system together with a data privacy protection mechanism is one of the most important issues in NoSQL databases. In this paper, we investigate the attribute based access control model (ABAC) and use it as the main access control system in NoSQL databases. Moreover, we propose and implement a comprehensive framework for enforcing attribute-based security policies stored in JSON document together with a data privacy protection mechanism in the fine-grained level. We use Polish notation for modeling conditional expressions (i.e., the combination of subject, resource, and environment attributes) so that ABAC policies can be flexible, dynamic and fine grained. Moreover, for data privacy protection, privacy rules of the policies are constrained not only by access and intended purpose but also by subject, resource, and environment attributes as well as data disclosure level. The experiment is carried out to show the relationship between the processing time for access decision together with the privacy protection mechanism and the complexity of access and privacy policies.

Stem removal is necessary for fresh chilli fruit processing, especially in the Mekong Delta region. In previous studies, the destemming method using clamping belts has been done which allowed to grip and completely separate the stems. However, the control of the gripping force has not yet been implemented, thus causing unable to clamp the stems, or clamping strongly to break the stems. This study focuses on building a force model to control the destemming process, helping to improve the success rate. The mathematical relationship between the gripping force and the measured force on the sensor has been shown. The experimental model was set up and run to evaluate the working ability. Tests were carried out on 1,000 chillies with a successful rate of up to 96.2%. In further studies, this model would be extended to design a destemming system.

In the process of machining mechanical products, high productivity machining and small roughness of the product surface are desirable in all cases. In this study, a new approach to improve milling productivity will be presented on the basis of ensuring the minimum required surface roughness. The experiments have been conducted for 40CrMn steel using TiAlN coated cutting tools. The experimental matrix of 15 experiments has been designed using Box-Behnken method. A regression model showing the relationship between surface roughness and cutting velocity, feed rate and cutting depth has been set up. Sub-regression models representing the relationship between surface roughness and each input parameter have also been created. From these models, the effect of cutting parameters on surface roughness has been determined. The main objective of this study is to determine the value of cutting parameters to improve the cutting productivity while ensuring the minimum surface roughness value.

Sandwich is a material widely used in industries, such as automotive, navy, construction, aviation. It has a high stiffness-to-weight ratio, so it meets the requirements of industrial part weight reduction. In this study, we built a numerical model to analyze the behavior of composite sandwich panels subjected to vibration. However, the sandwich panel was in the form of a shell, so it took a lot of time to perform simulations and build a CAD model. To solve this problem, we proposed a numerical model by homogenization method for this composite sandwich panel. This model was implemented in the finite element software Abaqus and confirmed by comparing the finite element simulation results of the vibration test of the 3D-model and homogenization model.

Nowadays, Fused Deposition Modeling (FDM) technology has been broadly applied in many fields. However, one of the major limitations of the current FDM technology is the accuracy of dimension of the product. This is an important criterion in evaluating the accuracy of surface quality of mechanical products. Therefore, the improvement of the accuracy of dimensions of 3D printed products by FDM technology is indispensable. In this study, the effect of forming parameters on the accuracy of the width dimensions of plastic materials PolyLactic Acid (PLA) parts that were manufactured by FDM technology was analyzed. The experimental planning method and design of experiment (DOE) were applied to define the optimal forming parameters for enhancing the accuracy of dimensions of PLA products by FDM technology.

It is well-known that the amount of glucose in the blood that exceeds the normal sugar blood range can cause diabetes, which is one of the most dangerous diseases that thread human health. Amongst a lot of methods that have been developed to measure glucose levels, electrochemical glucose sensors have attracted more attention due to their accuracy and efficiency. In our work, a simple, instant, and economical chemical process was conducted to deposit NiO nanostructures on the surface of a nickel foam electrode for non-enzymatic glucose electrochemical sensor. The morphologies and components of synthesised materials were characterised by field emission scanning electron microscopy and energy-dispersive X-ray spectroscopy. Cyclic voltammetry and chronoamperometry were used to measure glucose concentration based on the synthesised materials. The electrode showed a remarkably high sensitivity of 6.8 mA·mM−1·cm−2 and a low limit of detection of 5.7 µM. The results indicated that the fabricated electrode can be a potential candidate for clinical applications.

In this paper, a simulation model of the vehicle equipped with a 6-speed dual-clutch automatic transmission was built with the help of Simscape driveline/Matlab 2019 tools. The model consists of 4 subsystems: engine, dual-clutch transmission, control block, and vehicle body. Using the model allows determining the influence of structural parameters, working conditions on the vehicle’s kinematics and dynamics. Some simulation results of kinematics and dynamics of the vehicle when running on the ECE-15 driving cycle are also analyzed in detail in this paper.

The turbine shaft is an important part of the turbocharger structure. This part requires quite high hardness, especially when operating it needs high strength to ensure the working conditions with very high speed, pressure and temperature. This paper presents the research results of the effects of temperature and heat retention time at high tempering on the hardness and tensile strength of the turbine shaft in the HX40W model turbocharger structure made of 42CrMo steel.

The dynamic load acting on the vehicle has a variable value, it depends on the moving conditions, road quality and tire stiffness, etc. In this paper, the authors study on the effects of the tire vertical stiffness on dynamic load acting on DVM 2.5 truck. The method of structural separation multi-body system and the Newton–Euler equation are used to set the three-dimensional dynamics model. Matlab-simulink software is used to consider the effects of the tire vertical stiffness on dynamic load of DVM 2.5 truck. The results show that, when the tire vertical stiffness is increased, the maximum dynamic load acting on the tires, chassis and road rises and the transmission capacity drops. In order to ensure the dynamics safety and durability, a fully loaded DVM 2.5 truck is run on a class E road according to ISO 8608:2016, the speeds must be less than 50 kph and the tire vertical stiffness must be less than 912 kN/m.

Because of the lack of galvanic isolation, the leakage current causes problems in transformerless three-phase photovoltaic (PV) systems. The conventional three-phase photovoltaic inverter failed to limit the leakage current in a constructive way. In order to solve the leakage current problems in the conventional three-phase photovoltaic inverter, a three-phase transformerless H10 inverter is proposed by combining the conventional four-leg inverter of two switched-boost networks in this paper. The proposed three-phase transformerless H10 inverter has the major features as shoot-through immunity, boost voltage with one-stage conversion. Furthermore, a common-mode voltage of the proposed three-phase transformerless H10 inverter is kept constant during switching cycles. The operating principles for the proposed three-phase transformerless H10 inverter are presented. Finally, the proposed three-phase transformerless H10 inverter topology is tested, and the results validate the effectiveness of the proposed three-phase transformerless H10 inverter topology.

Managing procedure for charging and discharging battery system plays an essential contributor in improving the performance of energy storage system for example increment of utilizing batteries. This paper aims to develop a new hybrid genetic algorithm-based proportional integral (GA-based PI) controller with an adaptive neuro-fuzzy inference system (ANFIS) for the charging balance of batteries. The dataset is generated by using the GA-based PI controller, then a training strategy is introduced for the ANFIS controller. The proposed approach is evaluated by the GA-based PI controller and the PI controller based on Ziegler Nichols method.

In this paper, the tension and speed control problem of a rewinding web handling system are considered. Most of the design methods for tension controller of web transport systems require state and output variables feedback. However, when complex systems, as more variables as more feedback signals, need more sensors which makes the system bulky and expensive. The novel of the paper is to design a robust controller for the web transport system based on DSC technique to ensure high accuracy in the tracking and tension controller based on back stepping controller without using tension. The simulation results show the validity and effectiveness of the proposed control.

The simulation for dynamics of bus body in case of side rollover is applied in this study. Research methodology is digital simulating in Ansys Workbench software. In the results, deformation of bus body, in case of rollover at right angle, has been checked. Level of body deformation is determined by dynamic parameters are deformation value, equivalent stress to compared according to approved stress criterion of body material.

Tires have an important role in interaction between vehicles and the road because it is the only component of a vehicle contacting the road. Vehicle’s loading and running vibration depend on rubber’s elasticity and compressed air in tires.This article analyzes contact area of 4 different tire’s patterns including: flat pattern, longitudinal groove pattern, convex lug pattern of off-road vehicles and of trucks. Using Ftire model and simulation in Ansys Worbench software to determine average pressure Ph, frictional stress Fr in contact area, which causes compressive stress and tire pattern’s deformation. It then is transmitted to tires and body, causing tire’s damage.

A kinematic calculating and analyzing method for a robot moving on a horizontal bar using a four-bar mechanism is proposed. By using analytical methods, the kinematic model of the robot is included to examine parameters such as leg tilt, average moving velocity, position, and trajectory of the robot’s legs. Using the inversion mechanism method, the basic calculation can determine the movement of the mechanism on the bar during the operation.

This study was conducted to verify the working ability of the cam mechanism mechanisms with flat-face follower designed using envelope theory. The influence of the number of control points and the selection of construction curve for the designing process is verified and simulated using ADAMS software. To evaluate the capacity of the mechanism, kinematic parameters of the follower are also extracted for comparison with the initial designs.

In this article, research on the applications of artificial intelligence in implementing reinforcement learning is a subset of machine learning that deals with learning decisions from rewards given by the environment. Classic reinforcement learning algorithms are usually applied to small sets of states and actions. However, in real applications, the state spaces are of a large scale and this will bring the problems of the generalization and the curse of dimensionality. In this paper, we integrate neural network into reinforcement learning methods to generalize the value of all the states. Simulation results on the Gazebo framework show the feasibility of the proposed method. The robot can complete navigation tasks safely in an unpredicted dynamic environment and becomes a truly intelligent system with strong self-learning and adaptive abilities.

This paper proposes a decentralized control strategy that combines Sliding Mode Control (SMC) and Virtual Oscillator Control (VOC) to share the load power among Photovoltaics (PV) generations in islanded microgrids under different solar irradiation levels and load conditions. The SMC based controller of the DC-DC boost converter is used to regulate the DC link voltage. Meanwhile, VOC based DC-AC inverter is used to guarantee the load power-sharing in proportion to the rated powers, the RMS voltage regulation, as well as providing maximum power point tracking (MPPT) function when necessary. The proposed control strategy has the capability of seamlessly switching between different control modes without controller reconfiguration and the support from external devices such as energy storage systems (ESS). The performance of the proposed control strategy is validated in Matlab/Simulink.

Energy saving in Wireless sensor network (WSNs) is always critical since the networks facilitate many applications in different fields. In this paper, we study and analyze unequal clustering algorithms in the literature and propose a new algorithm that combines traditional unequal clustering algorithms and Compressed sensing (CS) techniques for further energy saving and balancing. In the proposed algorithm, sensor nodes are arranged into unequal clusters that the clusters closer to the base-station (BS) have smaller sizes compare to the ones farther from the BS. A greedy tree is proposed to link all cluster-heads (CHs) together as a tree. CS measurements are created at CHs to be sent via the tree to the BS. Based on a certain number of CS measurements achieved, the BS applies CS recovery algorithms to reconstruct all data collected from the network. Energy consumptions for data transmission in the network are analyzed, formulated. Theory and simulation results are provided for verification purposes. The results show promising points to prolong the network lifetime.

This article presents the construction of an intelligent automatic navigation system for mobile robots in a flat environment with defined and unknown obstacles. Programming tools used in the studies are the operating system for mobile robots (Robot Operating System – ROS). From the updated information on maps, operating environment, robot control position and obstacles (Simultaneous Localization and Mapping (SLAM)), we can calculate the motion trajectory of the mobile robot. The navigation system calculates the global and local trajectory for the robot based on the application of Actor-Critic (AC) algorithm. The results of simulation studies in the Gazebo environment and the experimental run on the real Turtlebot mobile robot showed the practical efficiency of automatic navigation for this mobile robot.

In this paper, to get the minimum gearbox volume of a worm helical gearbox, a new method related to the computation of three dimensions of gearboxes is proposed. In the study, the volume of a worm helical gearbox was considered as the objective of the optimization problem. In addition, many main design parameters, comprising the total gearbox ratio, the coefficient of wheel face width of the second stage, the allowable contact stress of the second stage, and the output torque, were discussed to examine their influences on the optimum gear ratios of the gearbox. The technique tools such as the screening experiment, regression, and variance analysis were used to evaluate the effect of the design parameters on the optimum gear ratios. Moreover, a regression model was established for simply computing the optimal gear ratio of the worm unit.

In this paper, a cascade-loop control system in 400-Hz inverter power supply based on unipolar sinusoidal pulse width modulation (SPWM) is proposed for the 400 Hz Ground Power Unit (GPU) in aerospace industry, to improve output voltage quality under the nonlinear load conditions. For the proposed control system, Deadbeat (DB) control, which provides the rapid response for the current especially in the digital system, is utilized in the inner current loop control and the resonant control is performed for the outer voltage loop to reduce the Total harmonic distortion (THD) of output voltage. The computation delay caused by digital processor is taken into consideration and done by using the phase delay compensation technique. The proposed system is tested in testbed systems with a 90-kVA experimental prototype using digital signal processing. The simulation and experiment results show the advantages and effectiveness of the proposed system with relatively small voltage deviation and total harmonic distortion.

In this paper, the particulate silver coating containing nano-silica for biomedical implant was created by the electroplating technique. The characterization of the coating was assessed via its weight, surface morphology images, the concentration of silver ions release in the simulated body fluid (SBF), and the anti-bacterial properties of the silver coating against Escherichia Coli (E.Coli) bacteria. The experimental results indicated that the weight and structure of the coating depended on the nano-silica amount adding to the plating solution. The plating solution containing the silica nanoparticles content of 0.1 g/L created the grain silver coating with a fairly uniform dispersion of silica nanoparticles on the silver particle surface. The nano-silica improved the adhesion of the coating. The study results also showed that the silver ion concentration release in SBF after 168 h decreased by 10 times in comparison with the non-nano silica coating. Simultaneously, these coatings still ensured their anti-bacterial ability of up to 99% in 60 min of exposure against E.Coli bacteria.

Wood bandsaw blades differ in thickness, width, length, and tooth configuration. These blades come primarily in the four tooth configurations such as standard, skip, variable and hook. When sharpening different bandsaw blades, it requires changing or adjusting the drive mechanism of blade sharpening machine. The drive mechanism today mainly uses a slider crank with a cam mechanism or combines two cam mechanisms. In order not to have to change the drive mechanism when sharpening different bandsaw blades, this article proposes a flexible drive. When combining movement of slider crank and cam mechanism, kinematics of drive mechanism must be tested to avoid the impact between bandsaw blade and grinding wheel. The kinematics are conventionally determined by using geometry and mathematical method under support of computer software such as Mathcad, Matlab for all working positions in a grinding cycle. This traditional method is not intuitive as well as consumes a lot of time of designer. This article builds the 3D model of slider crank and cam mechanisms, then simulates their movements to determine the kinematics. The simulation results allow to assess the quality of the drive system and calculate the dimensions of drive mechanisms.

In recent times, multiple Unmanned Aerial Vehicles (UAVs) have been utilized in numerous fields. Applications exploiting UAVs range from civilian to military applications. Multiple UAVs have been used for surveillance, monitoring, penetrating, or event detecting. In these applications, an ability of multiple UAVs to track an interested object plays a crucial role. In this work, a framework of cooperative tracking for a team of multiple UAVs is proposed. The proposed method consists of two main stages. First, an interested object is evaluated by computer vision techniques implemented on UAVs. Each UAV would have its own observation about the object. A consensus algorithm is used to synchronize sensing information of a whole team to decide whether the object is a target or not. In the second stage, a flocking algorithm is used to drive a UAVs team to track the target. Simulations in both cases static and dynamic targets are illustrated tracking performance.

Functionally Graded Materials (FGM) is the advanced material that covers the advantages of both metal and ceramic which contain FGM. Due to the perfect combination, FGM plate is widely developed with the requirement for the practical application to avoid the difficulties from conventional approaches. Consequently, the study establishes the database from analytical model and uses it for developing a machine learning model in the desire of finding an alternative model to predict critical buckling load of the plate. Such a machine learning model is crucial for predicting critical buckling load of the FGM plate without complexity of analytical developments or finite element resources. The Gaussian Process Regression model has been developed based on the database containing 1000 labeled samples created from the analytical model. The Gaussian Process Regression models with and without optimization process are compared and the outstanding of the model with the optimization algorithm is revealed. The proposed model is validated on both train and test set with the R-square values larger than 0.99 and errors are significantly low indicating that the proposed model exhibits the required ability.

The penetration of renewable energy sources (RS), energy storage, and demand response in energy systems arise challenges for energy management problems. Micro-grid with flexible regulation abilities provides an effective way to solve the problems of RS connected to main grids. This paper proposes a stochastic model in the optimization of demand response program (DRP) of micro-grids which allow simultaneously optimizes both the RS with different technologies and energy storage. The operation cost including costs for purchasing power from the utility grid, the operation cost of RS and energy storage along with emission cost and cost of DRP is minimized in each computed cycle. The uncertainty is modeled by probability density functions, divided into states by the clustering technique and then scenarios are generated by the scenario matrix and reduced in order to reduce the computational burden. The simulation results by the test system show that the proposed model is feasibility and the DRP has significant impacts on efficiency improvement of micro-grids such as reduction of energy cost and emission, and avoidance of connection devices investment.

The gear ratio is a main important factor that affects the size, the mass, the volume, and the cost of a gearbox. Therefore, in calculating and designing gearboxes, the determination of optimum gear ratios is of great interest. This paper introduces a study on determining optimum gear ratios of a two-stage bevel helical gearbox. To find the optimal gear ratios, a problem of optimizing the gearbox for getting the minimum gearbox volume was conducted. In this work, the influence of the input parameters, including the total gearbox ratio, the coefficient of the face width of the bevel and the helical gear sets, the allowable contact stress and the output torque and their interactions on the output, is evaluated. A simulation experiment was designed and conducted with the help of the Minitab R19 software. From the results of the work, regression models to find the optimum gear ratios were proposed.

This study aims to present the optimization process of partial gear ratios for three-stage bevel helical gearboxes based on the minimizing cost of the gearbox. Eleven factors considered as the input parameters are selected to investigate their influences on the responses. A simulation experiment is designed and carried out using a computer program. Regression models are proposed to predict the partial gear ratios of u2 and u3. In addition to input parameters, their interactions have important effects in which total ratio gearbox ratio (ug) have the most impact on both u2 and u3. Besides, proposed models of two responses are highly consistent with experimental results. The proposed regression equations are based on optimization cost problems.

This paper presents a study on determining the optimum input parameter when Wire Electrical Discharge Machining (WEDM) when cutting half round SKD11 tool steel with a radius of 7 mm. In this work, six process parameters, including the cutting voltage, the pulse on time, the pulse off time, the serve voltage, the wire feed, and the cutting speed were investigated. The influences of these parameters on the surface roughness of the workpiece after cutting were analysis. Finally, a set of optimum input parameters was proposed to get the minimum surface finish. It was found from the analysis results that the optimum experimental model was suitable for applying.

The gear ratio is one of the most critical parameters in a gearbox. It is directly related to many other technology parameters. Therefore, the object to be optimized in the gearbox design is often the gear ratio. This paper presents a calculation method to optimize the gear ratio u2 of a worm helical gearbox according the minimum gearbox’s cost objective function. In this study, a simulation experiment was conducted to learn the effect of the main design parameters on the objective function. Also, the influence of the design factors on the optimum gear ratio u2. Moreover, suitable regression models for the calculation of optimum gear ratios were proposed.

This paper presents the research results to determine the optimal partial gear ratios of the four-speed helical gearbox based on the cost optimization problem. To solve that problem, a simulation experiment with 13 input parameters was designed and conducted. The influence of the input parameters on the optimum gear ratios was evaluated. In addition, regression formulas to determine the optimum partial ratios to achieve the smallest gearbox cost have been proposed. These formulas are easy to use because they are all in the form of explicit functions.

During its service, marine structures may be damaged due to repeated impact loadings arising from various actions including ice/object impact and slamming. Since the aluminum alloy is a light and non-corrosive material, it is used in marine applications such as high-speed vessels. Several impact tests on aluminum alloy plates for investigating the response of structures have been reported in the literature. In this paper, a development of a finite element model was presented to study the response of aluminum alloy plates to repeated impacts. The numerical model was first validated through a comparison with the existing test data. Based on the material properties of the tested models, the strain hardening was defined using the proposed equations. Repeated impact loading was simulated by performing the calculation repeatedly, in which a deformed shape and residual stress/strain from the previous impact were considered in the consecutive impact events. After substantiation of the analysis method, further numerical simulations were carried out by varying several essential parameters such as striker mass and initial impact velocity to examine the impact response of aluminum alloy plates under repeated impacts. The results showed that lateral deformation of plates was accumulated, and impact forces increased when experiencing a repetition of impact loading regardless of the impact scenarios.

This paper introduces a multi-objective optimization study in Electrical Discharge Machining (EDM) of cylindrical shaped parts made of SKD11 steel. In particular, the multi-objective problem consists of two single objectives including the surface roughness (SR) and the electrode wear rate (EWR). In addition, four main parameters of EDM process including the pulse time, the pulse off time, the current, and the servo voltage were selected for this study. The Taguchi method and the gray relation analysis were used to evaluate the effect of the above parameters on the SR and the EWR. Also, an optimal set of input parameters to ensure simultaneous optimization of two objectives, the SR and the EWR, are completely consistent with the experimental data.

This paper presents the results of research on the effect of input parameters on the surface roughness (SR) when electrical discharge machining (EDM) of cylindrically shaped parts. In the study, the Taguchi method was used to design the experiment and analyze the results. Besides, the workpiece material is made from SKD11 tool steel, and four input process parameters, including the pulse time, the pulse off time, the current and the surve voltage were investigated. Influence of the input parameters on the SR was evaluated by the Analysis of Variance (ANOVA) method. Furthermore, optimal values ​​of the input parameters have been proposed to achieve the smallest SR.

This paper presents a study on the influence of input parameters on the electrode wear rate (EWR) when electrical discharge machining (EDM) of cylindrical shaped parts made from SKD11 steel. In this study, the Taguchi method was used to design and analyze the results of the experiments. In addition, the input process parameters including the pulse time, the pulse off time, the current, and the serve voltage were investigated. The influence of the input parameters on the EWR was evaluated by applying Analysis of Variance (ANOVA). In addition, optimal values of the input parameters have been proposed to obtain the minimum EWR.

After demolding, in order to get the final form for assembly or other functions, the secondary manufacturing processes are needed to remove the excess materials in the edge of CFRP parts. The machining process of CFRP composites is accompanied by the occurrence of defects induced. Hence, mastering the factors affecting induced defects is crucial. The aims of this study are to conduct the evolution of machining quality, characterized by the ten-point max, Rz when changing the process parameters. Three levels of feed speed and two levels of spindle speed are combined to generate a full experimental design. Both up and down milling is conducted to examine the effects of machining configuration on machining quality. It is found that spindle speed, feed speed and machining length, and machining configuration have impacts on machining quality. However, when milling at longer distance of 3.0 m, the effects of machining configuration is not clear.

To evaluate the effects of stearic acid on the dispersibility of zeolite 4A in polyethylene matrix, the master batches containing 20–40 wt% of stearic acid uncoated and coated zeolite 4A and the linear low-density polyethylene (LLDPE) films containing 3–7% stearic acid uncoated and coated zeolite 4A were prepared. The structural change of zeolite 4A which was modified surface with stearic acid was studied using IR spectroscopy. The dispersion of zeolite 4A in LLDPE matrix was evaluated using a scanning electron microscope (master batch samples) and optical microscope (film samples). The change in the melting temperature of LLDPE in the presence of 4A zeolite was evaluated by using differential scanning calorimeter (DSC). The mechanical properties of the film were evaluated according to ASTM D882. Surface-treated zeolite with stearic acid dispersed in the masterbatches and films better than untreated zeolite. Stearic acid did not change the melting temperature of zeolite 4A/PE master batches. The mechanical properties of the films containing stearic acid coated zeolite 4A were higher than those containing unmodified zeolite 4A.

Fused filament fabrication (FFF) is a well-known technique used to build 3-dimensional objects from thermoplastic materials. In order to make functional parts, the characterization of the printed part has become increasingly desirable. This study aims to study the mechanical properties of printed parts by doing experiments and data analysis through the design of experiments (DOE). The results indicate that those process parameters and their interactions significantly impact the mechanical properties of the printed parts. Further research is needed to identify other factors that could strengthen the effectiveness of printed parts.

Flexural strengthening of reinforced concrete (RC) beams using carbon fiber reinforced polymer (CFRP) sheets is a solution that shows many advantages in comparison to traditional strengthening solutions. The main goal of this study is to examine the effects of initial load on the effectiveness of strengthening by externally bonded CFRP sheets. Two identical beams were tested. One beam was used as a control specimen while one other beam was strengthened in flexure under sustained load. The value of the initial load was determined based on the cracking of concrete in the tension zone, with a crack width value is 0.3 mm. The obtained results have shown that for RC beams that are already cracked and deformed under sustaining loads, the effectiveness of CFRP strengthening can be demonstrated by the significant increase in the flexural stiffness and the load-carrying capacity of the strengthened RC beams.

The method of navigation is a very important factor that decides the flexibility and accuracy of the AGV in different operating environments. With each method of navigation, we have different techniques for determining the position and angle of the vehicle. In this research, by fusing data from sensors, the angle, direction and position of the AGV then are estimated by the data of the inertial sensor, encoder and calculated by the Kalman filter algorithm. In addition, the minor inaccuracy in measurement of angle, direction and position are corrected when the AGV passes through the magnetic reference points embedded under the floor based on the virtual paths. The simulation results have proved the accuracy of the proposed algorithm.

The conventional three-phase current source inverter (CSI) suffers from the open-circuit problem. In CSI operation, the overlap-time in the gates signals needed for safe commutations causes the distortion in the output current waveforms. This paper proposes a new three-phase switching-cell current source inverter, called H6-SC-CSI. Based on switching-cells, the inverter reliability is enhanced because open-circuit concerns are eliminated, and the voltage over-shoot at turn-of is reduced. In the operation of the proposed CSI, switch overlap-time intervals can be minimized or eliminated. Therefore, the total harmonic distortion (THD) of the output current is reduced. A 1.2-kW prototype of the proposed inverter is designed and tested.

Users’ mobility has a huge impact on the performance of cellular networks. Acknowledge users’ multiple next locations plays an important role in various aspects which can be mentioned as helping the base stations to pre-calculate and allocate the resource to users faster and more efficiently, shortening the duration of the handover process, reducing significantly the network data congestion, and increasing the overall users’ satisfaction. In our article, we focus our attention on multiple users and multi-position ahead prediction for femtocells and small cells, typical of 5G infrastructure. We use Autoregressive Gated Recurrent Units (AR-GRU) to perform the prediction based on acknowledging users’ trajectories. We use Simulation of Urban MObility (SUMO) to create our own users’ trajectory datasets to train and test the models. In order to prove the effectiveness of the model, we compare its performance with Autoregressive Long Short-Term Memory (AR-LSTM), Deep Learning Neural Network (DNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) models. Then we use the models in two more different datasets from two different simulated regions to prove the ability to work in different contexts.

This paper introduces a study on optimizing the powder-mixed electrical discharge machining (PMEDM) for processing cylindrical shaped parts made of SKD11 steel to get the maximum material removal speed. In the study, an experiment was carried out with the use of the Taguchi method for experimental design and analyzing the results. Six input parameters, including the powder concentration, the powder size, the pulse on time, the pulse off time, the current, and the servo voltage, were selected to study the impact of the input factors on the MRS. In addition, optimal values of the input parameters to achieve maximum MRS have been proposed.

In industries, induction motors (IM) are widely used because of their simple structure, low cost, and reliable operation. However, the working efficiency of the IM motor is greatly affected by the quality of power supplied from the grid. The current industrial power grid is increasingly unbalanced due to load unbalance and voltage becomes increasingly non-sinusoidal due to the use of more nonlinear loads and power electronic converters. This degrades the power quality leading to a decrease in the efficiency of the IM. This article simultaneously studies the influence of two factors voltage unbalance and harmonics on IM performance efficiencies such as power loss, efficiency, speed, torque, and ripple parameters in IM. In addition, the content of the article also shows the influence of different harmonic components on the working mode of the IM motor. The research results were simulated using Matlab-Simulink software, there are important data for users to have appropriate operating solutions to improve the performance and life of the IM motor in different operating modes.

The influence of dressing parameters on the tool life of grinding wheel when grinding of internal cylindrical grinding of hardened SKD11 steel was studied in this article. Also, the coarse dressing depth, the number of coarse dressing, the fine dressing depth, the number of fine dressing, the non-feeding dressing, and the dressing feed speed can be considered as input parameters. Besides, the Taguchi method and the Analysis of Variance (ANOVA) method were applied to find the optimum set of dressing parameters which can improve the tool life of the grinding wheel. The results reveal that the tool life of grinding wheel will maximize at 16 min when the set of dressing parameters is optimum.

In recent years, silicon wafer based solar cells have dominated the market due to their long lifetime and higher photovoltaic efficiency in power generation. Wafers are mainly manufactured by slicing Si ingots using fixed diamond wire sawing process (DWS). This paper presents an investigation of the influences of diamond abrasive density on the material removal mechanisms in DWS based on the model of wire profile model. Results show that the abrasive density directly affects the distribution of cutting depth in different cutting zones. While brittle material removal is still the major way of material removal at the bottom of the wire heading to the ingot, material removal at the side shifts to pure ductile cutting mechanism happens when the abrasive density increases. The developed model could be useful in determining combinations of sawing parameters with given abrasive density for obtaining better DWS process with high efficiency and good wafer surface quality.

C250 steel is a Nickel-based alloy steel with really high hardness, strength and ductility. An excellent feature of this steel is its ability to limit surface cracks during machining. In this article, a study on the influence of cutting parameters on surface roughness when grinding this steel is presented. Segmented grinding wheels with 18 grooves were used and the experimental process was carried out with a total of 15 experiments in the form of a Box-Behnken design matrix. At each experiment the parameters were selected as the input parameters including the velocity of workpiece, the feed rate and the cutting depth. The surface roughness has been selected as the output parameter of the experimental process. The analysis of experimental results has determined the influence of the input parameters on the surface roughness. A regression model showing the relationship between the input parameters and the surface roughness was also developed. Genetic Algorithm (GA) was chosen as the instrument to solve the optimization problem. The results of the optimization problem have determined the values of the cutting parameters to ensure the minimum surface roughness. The experiments to verify the optimal results of the cutting parameters were also conducted. The results show that the optimal value has been achieved with a very high reliability degree, in which the deviation between the experimental and predicted values is only 5.79%. Some further directions when studying the grinding technology with segmented grinding wheel have also been proposed in this article.

In this paper, a mathematical model describing the vehicle dynamics is built based on a nonlinear tire model and vehicle dynamic model of longitudinal and lateral motion. The influence of two drivetrain layouts FWD and RWD on vehicle lateral dynamics are considered. The analysis is done in MATLAB/SIMULINK environment. The results confirm that the inertia and lateral forces generated at the tires when the vehicle is cornering depend on many different parameters, in which these forces have a proportional relationship with the vehicle velocity and steering angle. The greater the vehicle velocity and/or steering angle, the greater the inertia and lateral forces generated. Besides that, when cornering, the lateral forces of the tires and the inertia forces in the longitudinal and transversal directions of the FWD vehicle are greater than those of RWD vehicle.

In this paper, the results of a multi-objective optimization problem of electric discharge machining (EDM) of cylindrically shaped parts are reported. Two objectives, surface roughness (SR) and material removal speed (MRS), were selected for the multi-objective problem. In addition, SKD11 steel and 4 main EDM parameters, including the pulse on time, the pulse off time, the servo current, and the servo voltage, were investigated. The influence of these parameters on the SR and the MRS was analyzed using Taguchi and Gray Relation Analysis methods. Moreover, the optimal input factors to ensure simultaneous two targets, the SR and the MRS, have been shown. The proposed model has been also evaluated with the conclusion that it is completely consistent with the experimental data.

In dewatering vibration screen, increasing the sieving efficiency plays an important role for mining processes. This paper proposes the influence of the input parameters on the sieving efficiency for dewatering vibration screen systems. The input parameters include the frequency of cyclone motor, the frequency of vibrating motor, and the inclination angle of vibrating screen. The experiment design was conducted based on the Taguchi method. By using ANOVA analysis, the effect of the input parameters on the sieving efficiency was evaluated. Moreover, the optimal input parameters were found in order to maximize the sieving efficiency. The analysis results were examined with the experiment results. The difference between analysis and experiment is 1.18%. For this, the analysis result is significant for predicting the sieving efficiency of the dewatering vibration screen system.

In this paper, the results of a study on the influence of process parameters on surface roughness (SR) when powder-mixed electrical discharge machining (PMEDM) of cylindrical shaped parts of SKD11 steel are presented. In this work, an experiment was performed with the use of the Taguchi method for experimental design and result’s analysis. In the experiment, six input parameters, including the powder concentration, the powder size, the pulse on time, the pulse off time, the current, and the servo voltage, were investigated. The effect of the input parameters on the SR was evaluated by analysis of variance (ANOVA). In particular, optimal values of the input parameters to achieve the minimum SR were found.

The shunt reactor plays an important role for high and super-high voltages in transmission and distribution systems. It is used to absorb excess reactive powers generated by capacitive powers on the lines for no-load or low-load cases. In addition, it is also an important component to balance reactive powers in the system, to avoid overvoltage at the end of the lines and to maintain voltage stability at the specified level as well. In order to reduce the magnetic flux density and avoid saturation of the magnetic circuit, the reluctance value has to be increased by air gaps along the iron core. This leads to decreasing the influence of fringing fluxes around the air gaps. Non-magnetic materials are often used at the air gaps to separate between iron core blocks. The fringing flux departs and re-enters the lamination perpendicularly, thus the core blocks of a large oil-immersed shunt reactor are generally made from radially laminated silicon steels. In this paper, the correction of the distance between the air gaps is proposed to reduce the fringing flux and the value of the winding inductance of shunt reactors. All parameters of the shunt reactors are calculated via an analytic method based on the theory of magnetic circuit model, then a finite element method is used to compute and simulate the winding inductance for changing the distance between the air gaps.

In high speed cam mechanism, dynamic characteristics are issues that are always taken care since these affect the vibration of cam systems. This paper deals with a knot vector optimization of NURBS for high speed cam in order to minimize contact force between a cam and follower. The NURBS curve is used for displacement motion of the follower. The cam motions are improved based on the optimization of the contact force. The influence of the knot vector on the motion curves (displacement, velocity, acceleration and jerk) was investigated. The results demonstrate that the kinematics and dynamics of high speed cam mechanisms were improved.

With the wide applications of composite materials, virtual simulation tools become a big matter of concern in the new development process to predict the behaviors of materials before fabricating. The mechanical properties, behaviors of composites are strongly dependent on their microstructures. To link the gap between microstructure to macroscopic properties, the homogenization technique is used. Conversely, the localization technique is utilized to investigate the behavior of constituent materials at microstructure under macroscopic loading conditions. In this paper, the asymptotic homogenization (AH) method is applied to investigate the behavior of fibrous composite materials under different macroscopic strain conditions which are very complicated to carry out by experiment works. For demonstration, a short fiber reinforced plastic model with random fiber orientation, random fiber arrangement, and random fiber length is analyzed. The influences of strain conditions on this complex microstructure on the microscopic strain distribution are observed and visualized on any arbitrary cross-section. The results show that the high microscopic strain arises more in the case of coupled shear strain conditions through histograms, whereas the largest microscopic strain appears in the case of coupled transverse strain and shear strain conditions. This analysis is worthy of the discontinuous fiber composite material design, initial damage prediction, and damage propagation analysis for further steps.

Model Predictive Control is an advanced control strategy that is suitable for multi-target optimal control problems with multiple inputs and multiple outputs that has been applied to many fields. This paper presents an optimal control design method based on the model for the active suspension system, including building the control structure, define the input and output states of the system and the signals constraints. Simulation examples of the control systems with specific parameters are also presented in the paper. The simulation results show the effectiveness of the proposed method.

During clutch engagement, a large amount of heat is generated. This high temperature adversely affects the working efficiency of the clutch: increased wear, thermal deformation, surface cracking, even damage to friction surfaces. Therefore, to improve the working life and efficiency of the clutch assembly, the study of heat generation and heat distribution is a necessary task. In this study, the author built a diagram describing the heat generated and its propagation in the clutch. Conducting surveys according to typical exploitation scenarios of automotive dry-clutch, the authors estimated the heat generated at the main components: flywheel, friction lining, and pressure plate. The results show that the relative sliding velocity and the engagement time have a great influence on the temperature generated in the clutch. Among them, the friction lining witnessed the highest temperature variation, and the temperature rise occurred faster when repeating the closed-opened clutch process many times.

An accurate and fast estimation of cutting forces is necessary for improving the performance of five-axis milling. However, the engagement between cutter and workpiece is very complex and irregular, it represents the main challenge for the prediction of cutting forces. This research aims to present a cutting force model of five-axis ball end milling, in which the effects of lead and tilt angles are investigated. The simulation results show that the resultant cutting force and total engagement area between cutter and workpiece are increased rapidly when the tilt and lead angles are close to zero. The cutting forces under different tool orientations are analyzed. The results of the proposed approach are successfully evaluated by the existing model.

Increasing the quality of workpieces and tool life is essential in grinding processes. This paper proposes a grey relation method to optimize surface roughness and wheel life in external cylindrical grinding SKD11 steel. The parameters comprising the rough dressing depth of cut, the number of rough dressings, the finish dressing depth of cut, the number of finish dressing, the dressing number without the depth of cut, and the longitudinal feed rate were evaluated by the grey relation coefficient at different levels. The optimum parameters were found based on the highest value of the grey relation coefficient in each factor at different levels. The results are reliable due to the combination with examining the influences of these parameters on the output responses, i.e., surface roughness and wheel life. Applying the optimal values of these parameters in external cylindrical grinding SKD11 steel the surface roughness, and the wheel life respectively obtain 0.143 μm and 14.5 min.

AA7075 aluminum alloy has the same hardness as steel but its weight is only about one-third that of steel. Thanks to this outstanding advantage, this material is widely applied in many different fields, especially in the field of automobile and aviation. Therefore, it is very necessary to study the multi-objective optimization when machining this material. In this article, a study on multi-objective optimization when drilling this material is presented. The experiments were conducted in accordance with a matrix designed by the Taguchi method. Spindle speed and feed rate were two parameters of which optimal values should be determined. Reference Ideal Method (RIM) was used to solve the multi-objective problem. The purpose of this study is to determine the values of the above two cutting parameters to simultaneously ensure the maximum value of Material Removal Rate (MRR), the minimum value of Diameter Error (DE) and the very minimum value of Roundness Error (RE). In addition, the effect of cutting parameters on DE and RE was also discovered. Finally, the directions for further study were also mentioned in this paper.

This paper presents the results of a multi-objective optimization study when powder-mixed electrical discharge machining (PMEDM) of cylindrically shaped parts made of SKD11 steel to achieve the maximum removal speed (MRS), and minimum electrode wear rate (EWR). To carry out this study, an experiment was conducted with six input parameters, including the powder concentration, the powder size, the pulse on time, the pulse off time, the current, and the servo voltage. Besides, the Taguchi method combined with the gray relation analysis (GRA) method was used to design experiment, and analyze experimental results. The impact of the input parameters on the MRS and the EWR was analyzed. In addition, optimal input parameters to get the maximum MRS, and the minimum EWR simultaneously were found.

This paper introduces a study on multi-objective optimization of powder-mixed discharge machining (PMEDM) for machining cylindrical parts made of SKD11 steel to achieve the minimum surface roughness (SR) simultaneously and maximum material removal speed (MRS). In this study, an experiment was conducted with the design and analysis of the results according to the Taguchi method. Six input parameters including powder concentration, powder size, pulse generation time, pulse off time, servo current and voltage were selected to study the influence of input factors on SR and MRS. In particular, the optimal values of the input PMEDM parameters to achieve the minimum SR and maximum MRS simultaneously have been proposed.

In this study, a multiple criteria decision making study is presented when turning S55C steel. The experimental process was conducted in the order of the Taguchi matrix with a total of 16 experiments. At each experiment, the coolant type, cutting velocity, feed rate and depth of cut were changed. The cutting tool used was a TiCN coated insert. Surface roughness, Material Removal Rate (MRR) and Tool Wear (TWR) were selected as the criteria for evaluating the turning process. The Vikor method was applied to determine the type of coolant and the value of cutting parameters to simultaneously ensure three criteria: minimum surface roughness, maximum MRR and minimum TWR. The orientation for further research has also been recommended in this article.

1655 steel is a medium carbon steel, used very commonly to manufacture parts such as shafts, gears, or rollers. Therefore, the study on multiple objective optimization when machining this type of steel will contribute to improve the efficiency of the production process. In this study, the milling of this steel was performed by the Titanium Nitride-coated cutting tool. The Taguchi method was applied to design an experimental matrix. In each experiment, parameters including nose radius, spindle speed, feed rate and depth of cut were changed. The surface roughness (SR) and flank wear (VB) were measured and material removal rate (MRR) was calculated. The Topsis method was also applied to solve the multiple objective optimization problem. The results determined the value of the nose radius and the cutting parameters to simultaneously ensure the criteria as the minimum SR, the minimum VB and the maximum MRR.

In the present work, we have investigated the influence of gold nanoparticles (nanogold) on redox reactions of iron/air battery anode. The Fe2O3 nanoparticles and gold nanoparticles were used as iron sources and additives, respectively. Acetylene black carbon (AB) was introduced as an additive to improve the conductivity of the iron oxide electrode. A blend of Fe2O3 and gold nanoparticles (Fe2O3/Au) was prepared by mixing Fe2O3 nanoparticles in a solution of pure gold nanoparticles. The grain size and morphology of gold nanoparticles were observed by Transmission Electron Spectroscopy (TEM) whereas the particle size, morphology of Fe2O3 and Fe2O3/Au mixture were examined by Scanning Electron Spectroscopy (SEM). The electrochemical characteristics of Fe2O3, Fe2O3/Au, and Fe2O3/Au/AB electrodes in alkaline solution were investigated using cyclic voltammetry (CV) measurement. Results suggest that Fe2O3/Au mixture has a uniform distribution of gold nanoparticles on an iron surface and thereby improves the cyclability of Fe2O3/Au electrode. The positive effect of AB on the electrochemical properties of Fe2O3/Au/AB composite electrodes was revealed via improved cyclability of Fe2O3/Au/AB electrode as evidenced by higher redox reaction rate and larger redox current.

The paper proposes a control strategy using integral backstepping control for an axial flux permanent motor. Filters are integrated into each control design step to eliminate tracking errors and undesirable effects. Moreover, the controller needs to reduce the effect of load and disturbances, and the high-gain observer is performed to estimate the uncertainty components of the control system. As a result, the speed trajectory can be more effectively held at high speed and medium speed. Finally, the simulation results show that the proposed control system can obtain the prescribed output tracking transient performance and robustness for the system uncertainties.

This paper presents a method to design a linear state feedback controller with time-varying parameters for the differential-drive mobile robot to track a NURBS curve trajectory. First, the linear state feedback controller is designed based on a kinematic error model of the robot. Then, determine the time-varying parameters of the controller according to the varying angular velocity for the desired trajectory. A robot model has been experimental designed and manufactured for experimental verification of the proposed controller. The simulation and experimental results show that the kinematic controller developed by this study has high-performance trajectory tracking with minor tracking errors. Therefore, it shows can apply that the results of this research in many different fields.

Blasting system has been widely used in industry so far. The optimization to reduce the blasting cost is necessary. The current study presents on a method to optimize the replaced nozzle diameter made of aluminum oxide of blasting system. The solved issue is based on finding the objective function of minimizing the blasting cost. The Design of Experiment (DOE) method is applied using Minitab19 to investigate the influence of seven input parameters on the response, the optimum replaced nozzle diameter. According to the obtained results, it is known that the optimum replaced nozzle diameter is crucially/highest impacted by the initial nozzle diameter dN0. Furthermore, the interactions between input parameters also have important effects in which the initial nozzle diameter is the key factor when combined with others and has significant impacts on the response. In addition, the effectively suggested regression model is wholly suitable to the experimental data. With this result, it is simple to calculate the optimum replaced nozzle diameter.

This paper introduces the results of an optimization study on gear ratios for three-stage helical gearboxes based on the objective function of the minimum volume gearbox. To solve this problem, a simulation experiment is designed and performed using a computer program. In this work, eight main design parameters were selected to investigate their influence on the optimum gear ratios. In addition, regression models to calculate the optimal gear ratios u1 and u2 have been proposed. The study also confirms that these proposed formulas are well suited to the experimental data.

The turbine shaft is an important part of the turbocharger structure. This part re-quires not only high mechanical properties, precision but also high surface smoothness to ensure the working conditions with very high speed and tempera-ture. This paper presents the research results of optimization of grinding technol-ogy parameters to surface roughness and material extracting productivity of tur-bine shaft parts made of 42CrMo steel of the turbocharger structure.

A study on optimization of powder-mixed electrical discharge machining (PMEDM) when machining cylindrical parts made of SKD11 steel to minimize the electrode wear rate has been introduced in this paper. In the study, an experiment was conducted in which the Taguchi method was used to design the experiment and analyze the results. Besides, six input factors containing the powder concentration, the powder size, the pulse on time, the pulse off time, the current, and the servo voltage were taken to study their effect on the tool wear rate. In addition, an optimal set of input factors to limit the tool wear rate has been proposed.

In the production of black tea, the fermentation stage plays a key role Abstract: In the production of black tea, the fermentation stage plays a key role in determining the quality of the finished tea. The color will often change during each stage of the fermentation process. In order to assess the degree of fermentation of black tea, tea producers must observe the change of color directly with their eyes, until the color turns red and the fermentation process has reached. To be able to accurately determine the color of standard fermented tea by manual method is not high, resulting in substandard tea quality. In this paper, the author proposes a model to evaluate the fermentation level of black tea based on the computer vision system combined with the Random Forest (RF) model on the HSV chart. The database for analysis and evaluation was collected by the author directly from Song Lo black tea factory, Tuyen Quang province. Besides, the author also compares this algorithm with algorithms such as SVM (Support Vector Machine) and MLP (Multi Layer Perceptron) to see that the classification efficiency of the RF algorithm is the highest.

This study aims to present the results of an optimization study to find optimum partial gear ratios for two-stage bevel helical gearboxes based on minimizing gearbox cost. In the study, ten main design factors considered as the input parameters are selected to investigate their influences on the responses. Also, a simulation experiment is designed and carried out using computer program. It is found that in addition to the input parameters, their interactions also have important effects in which total ratio gearbox ratio (ug) have the most impact on the u2. Besides, a regression model was proposed to predict the second gear ratios u2. The proposed model is highly consistent to the experimental results. From this model, the other partial gear ratios of the other components are easily determined.

This work deals with the determination of optimum Wire Electrical Discharge Machining (WEDM) process parameters when machining half-round SKD11 steel with a radius of 7 mm for getting the maximum Material Removal Rate (MRR) . In this work, six input parameters, counting the pulse on time, the pulse off time, the cutting voltage, the serve voltage, the cutting speed, and the wire feed were examined. The impact of these parameters on the material removal rate of the machining process was investigated. Moreover, optimum process parameters to get the maximum MRR were found. It was also noted that the optimum parameters were appropriate for use.

Recently, the combined differential evolution and the Jaya algorithm (CDJ) was proposed for shape and size optimization of truss structures under multiple frequencies. However, its extended applications for such problems under transient excitations haven’t been investigated yet so far. Also, its performance still requires more insightful verifications and this study aims to perform CDJ on 26 famous mathematical benchmark functions. The obtained results of the above-mentioned problems reveal that CDJ gives the best performances compared with those of other algorithms available in the literature.

This work develops a Neural Network (NN) model for the prediction of the tensile modulus of carbon nanotube (CN)/polymer nanocomposites, based on experimental database. A data set composed of 282 configurations is collected from available resources. Considered input variables of the dataset are such as mechanical properties of separated phases, density of polymer matrix, processing method, geometry of CN, modification method at the CN surface, etc. while the problem output is the tensile modulus of nanocomposite. Parametric studies have been performed in finding optimum architecture of the proposed NN model.

In this study, we aimed to synthesize ZnO nanomaterial and applied it for phosphate removal in aqueous solutions. ZnO material was prepared by a sonochemical route which is a simple and efficient method for large-scaled production of ZnO in nanosize. The surface characteristics and material structure of ZnO were determined via using electron scanning microscopy and X-ray diffraction methods. Batch experiments were conducted for evaluating the adsorption capacity of ZnO material. The effects of solution pH, adsorption time, adsorbent amount, and initial phosphate concentration on the adsorption capacity were investigated to determine the suitable condition for phosphate removal. Results showed a high phosphate removal ability at a wide pH range of 3–7 after 90 min with an adsorbent dosage of 0.6 g/L. The adsorption of phosphate followed Langmuir isotherm with a maximum adsorption capacity of 100 mg/g. The removal of phosphate in wastewater of Lam Thao Fertilizers and Chemicals JSC (Phu Tho Province) was also conducted with a high removal efficiency of 88.75%.

This paper presents the results of research and test of the self-designed and manufactured rotary friction welding machine. Tensile test results show that the tensile strength of the material after welding is satisfactory according to the standards of the material; the elongation is within the elongation limit of the welding specimen; the yield limit is greater than the minimum yield limit of the material. The parameters of the welding equipment are guaranteed according to the design requirements.

This paper presents a method to design a compound non-circular gear (CNCG) train with an improved cycloid tooth profile. First, the research established a mathematical model describing the centrodes of the CNCG train to create a variable gear ratio function. Then, the tooth profile of non-circular gears in the CNCG trains is shaped by a rack cutter whose tooth profile is an improved cycloid. A CNCG train with a speed variation range from 1.4 to 5.8 has been experimentally designed and manufactured. A system of experimental equipment to determine the gear ratio function of the CNCG train based on the meshing between the gear pairs in the CNCG train has been manufactured. The experimental results show that the maximum error of the gear ratio function experimental compared to the theoretical one is 4.74%. It shows that the results of this research can be applied into practical systems that require speed variations.

Pedestrian vehicle safety accreditation is a mandatory requirement for all cars marketed in the European Union. Therefore, when researching and developing a new car model, all automakers must study to design pedestrian protection in collisions. In the process of research and development as well as pedestrian safety accreditation, there are a lot of impacting tests to evaluate pedestrian safety. As for bonnet top area, there are at least 18 tests of headform impact to bonnet top to evaluate pedestrian head safety. Since the number of positions selected for testing is finite and discrete, it is difficult to accurately conclude the pedestrian safety level for every position on the bonnet surface area. In this study, the four models of machine learning (ML) algorithm Linear regression (LIN), Support Vector Machine Regression (SVR), Extreme Gradient Boosting (XGB) and Artificial Neural Network (ANN) are applied to predict the safety level of every position on the bonnet top surface based on the data obtained from testing at several positions. In order to assess the predictive performance of ML model, the error metrics are used such as root mean squared error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). The GridSearchCV algorithm is also used to find the best hyperparameter of ML model. The results of this study will be very useful for the development of solutions to vehicle safety tests for pedestrians. LIN is the best model in predicting the HIC value of headform and bonnet collision.

In this article, robust control schemes are presented for time-varying trajectory tracking control of Wheeled Mobile Robots (WMRs) in the presence of disturbance. First, the robust model predictive control (RMPC) is implemented for the kinematic subsystem by solving the modified optimization problem with the fixed starting point. Second, the robust control is extended for the dynamic subsystem by the Backstepping technique and additional observer. This paper shows how to ensure the stability of the closed-loop tracking error system. The performance of the proposed robust control is verified through simulation studies using Casadi tool.

This paper presents a scheme to estimate continuous states of Discretely Controlled Continuous Systems where continuous plants with nonlinear dynamics are controlled by discrete controllers that generate discrete control signals depending on discrete measurement events occurred at an irregular time. The aim of the estimator is to compute the continuous states of such systems from these measurements in order to provide the full information of the continuous states so that the discrete controller can extract suitable inputs to issue to the plant. The proposed state estimator is a modified version of the Unscented Kalman Filter (UKF). Upon receiving discrete measurement events, the estimator computes the estimated state and the covariance of the estimation error from previous measurement events according to the known nonlinear dynamic, control signals, and transformed sigma points. The next step is to incorporate the measurement value at present discrete events into the estimated state and the estimation covariance. The approach is verified by applying it to the water three-tank system built in MATLAB Simscape Fluid Toolbox.

This work presents a study on the behavior of stress corrosion cracking (SCC) phenomenon in pipeline steels for sour service in near-neutral media. SCC tests under static stressing conditions were performed in planar steel samples using a Cortest proof-ring coupled with a fabricated cell containing near-neutral pH solution as a corrosive medium, which simulates the soil conditions, to observe the cracking initiation stage. Characterizations of the steel samples using surface techniques such as SEM, EDS, and Raman spectroscopy show that the presence of nonmetallic inclusions takes place as pitting sites (to form corrosion pits), which constitute the most susceptible sites for SCC crack initiation. SEM images taken on the steel sample surfaces exhibit both SCC transgranular and intergranular crack types in near-neutral media. Although the obtained results are interesting, further study is necessary to evaluate and confirm the role of inclusions in SCC initiation mechanisms.

In industry, sandblastinghas been used with significant demand for surface preparation for painting, engraving, etc. During sandblasting, the replacement of the nozzle is a regular practice. However, optimizing the nozzle replacement has not been given sufficient importance. In this work, the determination of optimum replaced aluminum oxide nozzle diameter for minimizing cleaning cost was carried out. Three main input parameters, including the time for changing a nozzle, the nozzle wear rate per hour, and the compressor power, were selected to determine their impact on the cleaning costs. Besides, the Taguchi method was used for the experimental design and results’ analysis. The results show that the compressor power is the factor having the greatest impact on cleaning costs. Furthermore, the minimum cleaning cost were determined by the optimal parameters of the sandblasting process. The results of this study are a good experience for sandblasting processes using aluminum oxide nozzles.

AISI 1045 steel is considered the most popular steel type for machining mechanical products which is most often used to manufacture parts such as shafts, gears, forks, etc., … Therefore, the improvement of productivity and quality when machining this steel type is highly necessary to be studied. In this article, a study to improve the productivity when turning this steel type on the basis of ensuring the minimum surface roughness is presented. The experiments have been conducted in the order of Central Composite Design (CCD) matrix on CNC lathes and TiAlN coated inserts. From the experimental results, Response Surface Methodology (RSM) has been applied to build a regression model representing the relationship between surface roughness and cutting velocity, feed rate and cutting depth. Sub-regression models representing the relationship between surface roughness and each cutting parameter have also been set up. Since then, the charts showing the effect of each parameter on surface roughness have been built, as well as the values of cutting parameters have been determined to improve machining productivity while ensuring the minimum surface roughness. A number of verification experiments have been conducted and it is found that it is possible to increase the productivity by approximately 2 times, while the surface roughness is merely increased by 0.08 μm.

This paper presents a method of subordinate control with compensator based on a neural network for nonlinear electric drives of exoskeleton. The development of a dynamic model of an exoskeleton-human includes five links of two legs and a body, taking into account nonlinear electric drives of each joint. The neural network is used to approximate the nonlinear elements of the object model based on the dynamic error of the joint angles of the lower limb exoskeleton. Additionally, a robust element is used to correct the approximate error of the neural network in the control system. The convergence and asymptotic stability representations of the control system are proved on the basis of Lyapunov’s theory. Also, the results of the experiment were obtained to illustrate the effectiveness of the proposed control strategy in the Matlab/Simulink program, including comparison with a subordinate controller without compensator.

In this study, we report a fast and simple method for synthesis biochars from biomass sugarcane bagasse as a raw material. The biochars material possesses a good porous structure after one-step carbonization in a normal anaerobic furnace with an amorphous phase and a good specific surface area of 272.75 m2 g−1. The sugarcane bagasse-derived biochars show a harmonious agreement with the gel polymer electrolyte via electrochemical investigation. The electrical double layer supercapacitor cell demonstrates a good charge-discharge rate capability and also good specific capacitance. The porous biochars obtain electrode specific capacitance of 48 F g−1 at a current density of 2 A g−1 and the maximum energy density is about 7.71 W h kg−1 at a power density of 1028 W kg−1. This study provides a promising route for recycling waste biomass in energy storage applications.

A steel cylindrical grinding process has been carried out in this study, in which 1066 steel was employed as the experimental material and an aluminum oxide grinding wheel was utilized. The experimental matrix has been designed in the form of Central Composite Designs (CCD) with four input parameters, including cutting velocity, workpiece velocity, feed rate, and cutting depth. The surface roughness has been selected as the output parameter of the grinding process. The analysis of the experimental results using Pareto chart has determined the effect of the input parameters on the surface roughness. A regression model showing the relationship between the surface roughness and input parameters has been set up. In order to improve the accuracy of the surface roughness model, two data transformations of Box-Cox and Johnson have been applied to build two more surface roughness models. These three roughness models have been used to predict the surface roughness and those predictions have been compared with experimental surface roughness. Through the comparison criteria including coefficient of determination R2, adjusted coefficient of determination R2(adj), and absolute percentage error (PAE), the roughness model with the highest accuracy has been determined. Finally, the direction for further studies has also been mentioned in this article.

Pedestrian headform impactor on the bonnet top to assess the level of pedestrian head injury in a collision is one of the mandatory tests for all vehicles sold in the European Union market. Therefore, many automakers research how to design a bonnet reinforcement structure for pedestrian head protection when developing a new model of vehicle. Each automaker has their own designs and the reality shows that the different models of vehicles have different structures of bonnet reinforcement. Several structural models of the pedestrian-friendly bonnet reinforcement have been introduced by automakers, but the basis or design rules have never been published. Previous studies have focused on stiffness as it is believed that bonnet stiffness is the main cause of head injuries in collisions. This study was carried out with the aim of exploring how the structural properties of bonnet reinforcement affect on head injury in collision beside the factor of bonnet stiffness. The results of this study will contribute to the basis as well as the principles for the design of a bonnet reinforcement structure for pedestrian head safety.

The turbine shaft is an important part of the turbocharger structure. This part requires high mechanical properties, precision, and surface quality to ensure the working conditions with very high speed and temperature. Heat treatment of turbocharger turbine shafts is still a secret of the companies, and very few studies on this subject have been published. Automatic heat treatment system with turbine shafts is introduced. However, such an automated production system is not suitable for the actual conditions of the research facilities. This paper presents the research results of the high tempering process to give the optimal parameters of the relative elongation and yield strength of 42CrMo steel as the turbine shaft of the turbocharger structure.

The linear attack is a new intrusion attack type that can change the normal operation of SCADA systems. It easily passes Kullback–Leibler (K-L) detection method. This paper presents the applied ability of the Cumulative Sum method (CUSUM) and Chi-squared (CHI2) to detect the linear attack in case the K-L method cannot detect. The object, which is attacked, is a wireless communication process from level sensor and temperature sensor to a controller in a thermal mixing tank system. By analyzing the tested results, which is implemented on simulation data, it shows that an appropriate range of threshold of both CUSUM and CHI2 methods can be chosen to detect the linear attack. In addition, the obtained results also show that the detection ability of the CUSUM method is better than that of the CHI2 method.