Variation Of Characteristic Parameters Research Articles

Effect of weakening characteristics of mechanical properties of granite under the action of liquid nitrogen

Liquid nitrogen fracturing and hot dry rock geothermal development are both emerging technologies in the field of energy. However, during the extraction of geothermal energy, it can cause the evolution of geological fractures, leading to the diffusion of groundwater and pollutants, thereby causing environmental pollution issues. Currently, geothermal energy has become a focal point in the global development of renewable energy. However, traditional hydraulic fracturing methods used in harnessing geothermal resources suffer from limitations such as limited fracture creation, uncertain initiation points, and environmental pollution. In contrast, liquid nitrogen has emerged as a promising reservoir stimulation technique, exhibiting significant effects on rock fracturing. In this study, we conducted three-point bending tests on granite samples subjected to liquid nitrogen treatment at temperatures of 300°C, with varying numbers of cooling cycles. Changes in fundamental mechanical parameters were analyzed. Additionally, through acoustic emission monitoring, we studied the variations in characteristic parameters of acoustic emissions under different cooling cycle conditions. Furthermore, based on the theory of energy evolution, we analyzed the energy evolution process during sample failure under different cooling cycle conditions. Using a compact scanning electron microscope, we observed changes in the microstructure of granite and analyzed the influence of cooling treatment on its surface characteristics and failure modes, thereby revealing the thermal damage process of granite. Moreover, by employing a non-metallic ultrasonic testing analyzer, we scanned the fracture surface morphology of granite and investigated the variations in fracture surface morphology features and surface roughness parameters caused by cooling treatment. The results indicate that liquid nitrogen cooling treatment can more effectively reduce the mechanical properties of rocks, and this effect is further enhanced at high temperatures. Under the condition of 300°C, after undergoing different cycles of liquid nitrogen cooling, granite will exhibit a more diverse macroscopic and microscopic structural failure characteristics, consistent with the expected formation of fluid flow channels in high-temperature rock formations.

Study on Continuously Weakening Mechanism of Heap Leaching Velocity of Weathered Rare Earth Ores with the Increase of Ore Burial Depth

The column leaching experiments, CT, numerical simulation and fractal theory were adopted to study the continuously weakening mechanism of the heap leaching velocity of weathered rare earth ores with the increase of ore burial depth. The variation characteristics of pore structure and the seepage law of solution in ore samples at different depths during leaching were explored, respectively. The results showed that the variation of characteristic parameters of the pore structure in the lower ore samples was the main reason for the decrease in the leaching velocity. For the lower ore samples after leaching, the number of pores with a pore volume of less than 0.01 mm3 and a pore radius of less than 0.8 mm increased, while pore connectivity, the fractal dimension of the pore shape, the ratio of pore length to width and pore throat length reduced. The solution paths of the upper and middle ore samples were concentrated while that of the lower samples were few, even interrupted. The pore pressure of the ore samples decreased after leaching, especially that of the lower ore samples. The research results are helpful to enrich the basic theory on the heap leaching of weathered rare earth ores.

Thermal degradation and kinetic studies of redwood (Pinus sylvestris L.)

AbstractIn this scientific paper, thermochemical conversion of redwood (RW) was studied. Using the thermogravimetric analysis' technique (TGA), the thermal behavior of RW samples was examined at four heating rates ranging from 5 to 20 K min−1 in inert atmosphere between 300 and 900 K. Two main objectives have been set for this study; the first one was the determination of the kinetic decomposition parameters of RW (Pinus sylvestris L.), and the second one was the study of the variation of characteristic parameters from the TG-DTG curves of the main RW's components, such as; cellulose, hemicellulose and lignin. The kinetic analysis was performed using three isoconversional methods (Vyazovkin (VYA), Friedman (FR) and Flynn-Wall-Ozawa (FWO)), Avrami theory method and the Integral master-plots (Z(x)/Z(0.5)) method to estimate activation energy (Ea), reaction order (n), pre-exponential factor (A) and model kinetic (f(x)) for the thermal decomposition of cellulose, hemicellulose and lignin components.The DTG and TG curves showed that three stages identify the thermal decomposition of RW, the first stage corresponds to the decomposition of hemicellulose and the second stage corresponds to the cellulose, while the third stage corresponds to the lignin's decomposition. For the range of conversion degree (x) investigated (0.1 ≤ x ≤ 0.7), the mean values of apparent activation energies for RW biomass were 127.60–130.65 KJ mol−1, 173.74–176.48 KJ mol−1 and 197.21–200.36 KJ mol−1 for hemicellulose, cellulose and lignin, respectively. Through varied temperatures from 550 to 600 K for hemicellulose, from 600 to 650 K for cellulose and from 750 to 800 K for lignin, the corresponding mean values of reaction order (n) were 0.200 for hemicellulose, 0.209 for cellulose and 0.047 for lignin. The pre-exponential factor's average values for three components of RW ranges from 0.08 × 1012 s−1 to 2.5 × 1012 s−1 (Ahemicellulose = 1.09 × 1012 s−1), 0.10 × 1014 s−1 to 0.28 × 1014 s−1 (Acellulose = 0.17 × 1014 s−1) and 3.07 × 1016 s−1 to 3.69 × 1016 s−1 (Alignin = 3.33 × 1016 s−1), respectively. The experimental data of RW had overlapped the D4, D2 and F3 in the conversion degree of 10–30%, 30–55% and 55–70% for the three components, respectively.

Axial compressive responses of concrete canvas and CFRP reinforced corroded concrete short columns

To evaluate the axial compression performance of corroded concrete short columns reinforced by concrete canvas (CC) and carbon fiber reinforced polymer (CFRP), a total of 16 specimen sets with different reinforcement forms and corrosion rates are designed and examined in this paper. Specimens are subjected to electrochemically-induced corrosion before being mechanically tested under the compressive load. The assessed variables are theoretical corrosion rate (0, 5%, or 10%), number of CFRP wrapping layers (0, 1, 2, or 3), and number of CC layers (0 or 1). Through the signal localization of acoustic emission (AE) and the variation in characteristic parameters, it is found that the presence of CC changes the failure morphology of the specimen and improves the uneven deformation of concrete in the core area. Also, under the same number of CFRP wrapping layers, the peak stress of the CC and CFRP jointly reinforced specimens is reduced by about 10% but has a more than 70% increase in the ultimate strain compared with those of CFRP reinforced only, which proves that the jointly reinforced method exhibits high plasticity deformation ability. With an increase in corrosion rate, compared with the uncorroded specimens, the peak stress of JC specimens decreases by more than 6.9% but the ultimate strain increases by more than 15.4%. The JC specimens’ peak stress and ultimate strain models are then determined through fitting, from which a good correlation with those observed is witnessed. The comparison shows that the model has good accuracy and can provide a theoretical basis for further research for CC- and CFRP-reinforced corroded concrete short columns.

Experimental and theoretical study on the association between entrainment vortex evolution and pressure oscillation of steam jet condensation

Condensation pressure oscillation of steam jet has great influence on direct contact condensation (DCC) equipment. Therefore, it is essential to reveal the microscopic mechanism of pressure oscillation of steam jet condensation. In this study, the association between entrainment vortex evolution and pressure oscillation of steam jet condensation is investigated. Firstly, the periodic variation of characteristic parameters of jet oscillation caused by periodic vortex shedding is obtained based on the image processing techniques. Secondly, by synchronous comparison between the pressure oscillation cycles and the jet parameters oscillation cycles, it is found that the periodic evolution and shedding of two-phase entrainment vortexes formed in the upper and lower mixing layers is the microscopic mechanism which causes condensation pressure oscillation. Specifically, the high-frequency pressure oscillation near the steam jet results from the high-frequency transverse oscillation of the steam jet which is caused by the periodic vortex evolution in the mixing layer and the periodic shedding of the vortex blob at the tail of the jet; the low-frequency pressure oscillation near the steam jet results from the low frequency oscillation of the whole steam jet caused by periodic shedding of the paired vortex blobs; the pressure oscillation in the downstream of the steam jet is caused by the condensation oscillation of periodic shedding vortex blobs. Finally, the dominant frequency distribution of condensation pressure oscillation under various test conditions is analysed. Combined with the vortex shedding model, a prediction equation of the dimensionless characteristic frequency St of the shedding vortexes is established. The predicted values had good agreement with the experimental results.

Experimental investigation and evaluation of influence of oxygen concentration on characteristic parameters of coal spontaneous combustion

Understanding the oxidation characteristics of coal spontaneous combustion and the variation of characteristic parameters is of great importance to further clarify the intrinsic mechanism of coal spontaneous combustion and to ensure safe production in coal mines. In this paper, the oxidation process of coal samples was tested at four oxygen concentrations of 21%, 15%, 10% and 5% using a programmed temperature rise experiment. Important parameters of coal spontaneous combustion, such as oxygen consumption rate, gas production rate and exothermic intensity, were calculated for the coal oxidation process. The relationship between coal temperature and oxygen concentration and the spontaneous combustion characteristics of the coal was analyzed and discussed in detail. The results show that oxygen concentration is positively correlated with the concentration of gas production. The oxygen consumption rate, CO generation rate, CO2 generation rate and exothermic intensity of the coal samples varied exponentially with temperature, due to the fact that the higher the temperature, the more intense the chemical reaction between coal and oxygen. The oxygen consumption rate and the exothermic intensity of the coal samples at different oxygen concentrations show a linear increasing relationship, which has been justified by previous investigations. A simple mathematical expression relating the oxygen consumption rate to the heat release intensity was developed and the associated proportionality factor was defined as the exothermic factor A, which was employed as an indicator for the initial determination of the intensity of the oxidation reaction of spontaneous coal combustion for different oxygen concentrations and coal types. The greater the oxygen concentration the greater the A, which can be expressed as a linear equation. For both coal samples selected for this paper, increasing the oxygen concentration increases the degree of oxidation reaction. However, Sample YQ is more sensitive to oxygen concentration than Sample CC, and the exothermic factor A at low oxygen concentrations (5-10%) is much lower than at high oxygen concentrations (15%-21%), so special attention should be paid to the prevention of coal spontaneous combustion at high oxygen concentrations by nitrogen and carbon dioxide injection during coal mining. Sample CC has a higher A at both low and high oxygen concentrations, and has a higher risk of spontaneous combustion in both oxygen environments. Comparatively, Sample CC has a higher risk of spontaneous combustion at low oxygen concentrations than Sample YQ. The research results are expected to provide some support for understanding the oxidation process of coal spontaneous combustion and preventing fire hazards in the coal mining industry.

Digital Simulation and Identification of Faults with Neural Network Reasoners in Brushed Actuators Employed in an E-Brake System

The aerospace industry is constantly looking to adopt new technologies to increase the performance of the machines and procedures they employ. In recent years, the industry has tried to introduce more electric aircraft and integrated vehicle health management technologies to achieve various benefits, such as weight reduction, lower fuel consumption, and a decrease in unexpected failures. In this experiment, data obtained from the simulation model of an electric braking system employing a brushed DC motor is used to determine its health. More specifically, the data are used to identify faults, namely open circuit fault, intermittent open circuit, and jamming. The variation of characteristic parameters during normal working conditions and when faults are encountered are analysed qualitatively. The analysis is used to select the features that are ideal to be fed into the reasoner. The selected features are braking force, wheel slip, motor temperature, and motor angular displacement, as these parameters have very distinct profiles upon injection of each of the faults. Due to the availability of clean data, a data-driven approach is adopted for the development of the reasoner. In this work, a Long Short-Term Memory Neural Network time series classifier is proposed for the identification of faults. The performance of this classifier is then compared with two others—K Nearest Neighbour time series and Time Series Forest classifiers. The comparison of the reasoners is then carried out in terms of accuracy, precision, recall and F1-score.

Research of resonance vibrations of the system «Telescopic screw — bulk medium» caused by torsional vibrations

The article outlines the relevance of using the principle of telescopy in the process of creation screw conveyors, which nowadays are folded to obtain significant lengths, which makes their designs expensive and structurally unreasonably complicated. It has been shown an experimental equipment, which provides measurement results of the research process in a wide range with high accuracy in an automated control mode with the necessary data capture. Based on the constructed mathematical model, the dependences of the angular perturbation velocity on the physicomechanical and geometric parameters of the «telescopic screw — bulk medium» system have been obtained. Because of analytical relations describing the laws of variation of characteristic parameters for its oscillation resonance case have been received. It has been proved that for resonant oscillations, when there are significant angular velocities of rotation, the natural frequency of the bending oscillations is smaller and at the same time the amplitude of the transition through the resonance is smaller. The results of the amplitude of the transverse oscillations of the system for different values of the angular velocity of rotation in time during the transition through the internal resonance, which largely depends on the physicomechanical and geometric characteristics of the motion of the medium, have been presented.

Computational Study of Zigzag Spacer Design with Elliptical Cross-Section Filaments

The large energy consumption of membrane desalination process has encouraged researchers to explore different spacer designs using Computational Fluid Dynamics (CFD) for maximizing permeate per unit of energy consumed. In previous studies of zigzag spacer designs, the filaments are modeled as circular cross sections in a two-dimensional geometry under the assumption that the flow is oriented normal to the filaments. In this work, we consider the 45° orientation of the flow towards the three-dimensional zigzag spacer unit, which projects the circular cross section of the filament as elliptical in a simplified two-dimensional domain. OpenFOAM was used to simulate the mass transfer enhancement in a reverse-osmosis desalination unit employing spiral wound membranes lined with zigzag spacer filaments. Properties that impact the concentration polarization and hence permeate flux were analyzed in the domain with elliptical filaments as well as a domain with circular filaments to draw suitable comparisons. The range of variation in characteristic parameters across the domain between the two different configurations is determined. It was concluded that ignoring the elliptical projection of circular filaments to the flow direction, can introduce significant margin of error in the estimation of mass transfer coefficient.

Experimental research on bond anchorage performance of 1860-grade high-strength steel strands and lightweight aggregate concrete

To study the bond anchorage performance of 1860-grade high-strength prestressed steel strands and lightweight aggregate concrete, taking the cover thickness, anchorage length, stirrup spacing and matrix material as characteristic parameters, 10 groups of three specimens – a total of 30 test specimens – were designed and manufactured for pull-out tests. In these tests, the failure modes and the variation of bond strength of specimens were examined, and the influence of the variation of characteristic parameters on the bond anchorage performance of 1860-grade high-strength steel strand and lightweight aggregate concrete was studied. Optimal results were produced with a larger cover thickness and anchorage length, and smaller stirrup spacing. Based on the experimental data, we established the formula of ultimate bond strength and the formula of bond strength when the average slip is 1 mm, and a recommended formula for the anchorage length of components was devised incorporating current building design codes.

Research on the relationship between early surface deformation and microstructure evolution of Ni-based single crystal alloy

During the early service phase of Ni-based single crystal alloy (NSCA), the degree of its surface deformation is closely related to the service life. It is important to quantitatively characterize the surface deformation of NSCA from the microscopic scale. However, the studies on the quantitative relationship between the degree of surface deformation and the microstructure evolution of NSCA have not been found yet. Thus, we establish the theoretical relationship between the microstructure evolution of NSCA and its early surface deformation through nonlinear expression methods. The MD method is used to calculate the dislocation density change of NSCA in different crystal orientations, by which the variation of the characteristic parameter and the damage degree of NSCA are predicted. Moreover, the results of the MD simulation are consistent with the variation of nonlinear characteristic parameter obtained in the experiment, which further confirms the correctness of the theoretical relationship. This research will offer a theoretical basis for the predictive maintenance of aero-engine turbine blades.

Transformer Fault Prediction Method Based on Multiple Linear Regression

This paper mainly analyzes the transformer fault evolution rule. Meanwhile it analyzes the correlation relation between transmission and transformation equipment fault characteristic parameter and the fault. This paper establishes the fault characteristic parameter multi-factor forecast model and the equipment fault diagnosis model, which realizes the transformer fault occurrence probability, the fault type and the fault position real-time accurate forecast. It includes data acquisition and preprocessing, multi-factor prediction of fault characteristic parameters, correlation analysis of characteristic parameters and fault types, failure probability of various faults, equipment failure probability and fault diagnosis. In this paper, a transformer characteristic parameter prediction model based on environment and other factors is proposed. The example analysis of transformer characteristic parameter multi-factor prediction model based on multiple linear regression (MRL) shows that the multi-factor prediction model can effectively consider the influence of external factors on the variation of characteristic parameter, and the prediction accuracy is higher.

Experimental study on flame stability of biogas / hydrogen combustion

The flame stability of biogas blended with hydrogen combustion was experimentally studied in the constant volume combustion bomb. The variations of characteristic parameters of flame instability and effect of pressure and fuel component proportion on flame shape were analyzed. The experimental results show that the flame instability increases with the decrease of equivalence ratio, and the global flame stability decreases with increase of CO2 fractions. With increase of initial pressure of biogas and hydrogen mixture, Markstein length decreases, hydrodynamic instability decreases, but the thermal mass diffusion instability has no effect. The effect of increase of the hydrogen ratio on flame stability is more obvious, with the increase of initial pressure and hydrogen ratio together, both hydrodynamic instability and thermal mass diffusion instability increase. This research can provide experimental basis for the design and development of biogas blended with hydrogen engines.

Characterization of gas–solid fluidization in fluidized beds with different particle size distributions by analyzing pressure fluctuations in wind caps

For the operation of a fluidized bed, solid particle size distribution is related to fluid dynamic behaviors, heat transfer efficiency, combustion efficiency, and desulfurization performance. Measurement of pressure fluctuations has a great advantage for detecting fluidization and combustion conditions, due to its flexible adaption to any operating conditions. In this study, the measurement and analysis of pressure fluctuations in the inlet of a wind cap of fluidized beds were carried out, to investigate the effects of particle size distribution on the gas–solid fluidization behaviors. Pressure fluctuations in the inlet of central wind cap were measured at different primary air velocities in cold circulating fluidized beds with different particle size distributions. In order to obtain the corresponding characteristic parameters, pressure fluctuations were analyzed by the methods including standard deviation, power spectral density estimation, wavelet analysis, and homogeneous index. Based on these characteristic parameters, the effects of particle size distribution on the gas–solid fluidization behaviors in fluidized beds were systematically analyzed. Variations of characteristic parameters of pressure fluctuations were found to be related to the variations of the gas–solid fluidization behaviors, which were caused by changes in particle size distribution or particle sizes. The results of this study indicate that the proposed method is practical, and the research achievements can be used as a theoretical basis for the condition monitoring of particle size distribution or the detection of agglomeration in fluidized beds based on pressure fluctuations in wind caps.

An approach to investigate moiré patterns of a reflective linear encoder with application to accuracy improvement of a machine tool

The accuracy of a machine tool is based on the direct position feedback from its built-in encoders which accurately measure displacements of motion axes by moiré patterns. However, the posture of an encoder is altered by errors from the machine tool, resulting in six geometric deviations. A comprehensive analysis and scientific understanding on the influences of these deviations on moiré patterns are necessary. To investigate the influences, a simulation model of a reflective encoder is constructed to obtain moiré patterns, and four new methods are developed to identify characteristic parameters of the patterns. Variations in characteristic parameters caused by four geometric deviations are simulated and experiments are designed and performed. The results prove that the approach is able to assess the influences of geometric deviations. The approach can be used as a powerful aid for estimating impacts of geometric deviations and external errors on encoders to improve the accuracy of a machine tool.

Study on Temperature Characteristics of Frequency -domain Dielectric Spectrum of Capacitive Oil-paper Insulation Bushing Based on Extended Debye Model

In order to study the influence of temperature on the frequency domain spectroscopy (FDS) of the oil-paper insulation system, the 72.5kV bushing test model was fabricated according to the actual size, and the FDS of the bushing was tested at different temperatures. According to the test curves of the dielectric constant at different temperatures, the influence of temperature on FDS is analysed, and then the extended Debye equivalent circuit model is used to fit the FDS test curves at different temperatures. The characteristic parameters that could be used to characterize the temperature characteristics are extracted, and the relationship between the characteristic parameters and the temperature is established. The results show that dielectric constant tend to move in the high frequency with the increase of temperature. The parameters of the equivalent circuit model are sensitive to the temperature, the insulation resistance Rg and the maximum time constant branch parameter R1 show the exponential function with the temperature, the minimum time constant branch parameter R3 and the temperature show a power function relationship, so the variation of characteristic parameters can be applied to evaluate the influence of temperature on the FDS of the oil-paper insulation bushing.

Raman self-induced-transparency soliton trains in hollow-core photonic crystals

Periodic trains of non-topological dark and bright optical solitons are proposed as one of the possible nonlinear optical structures that could be generated during Raman transitions in nonlinear hollow-core photonic crystal fibers filled with gas. It is shown that Stokes-like probe fields, generated by stimulated Raman transitions upon propagation of the master pump in the hollow-core fiber, form a broadband spectrum, whose discrete branch is populated by several distinct localized periodic soliton modes with well-defined “quantum numbers”. Such soliton trains, which are intended to complement recently proposed single-pulse and single-dark solitons for multi-channel communication applications, can be formed by temporal quantum entanglements of the single-soliton fields. Attention is laid on a possibility to generate such soliton trains in the absence of Kerr nonlinearity, and total controllability of their shape profiles including their temporal periods and average widths is demonstrated through variations of characteristic parameters of the hollow-core photonic crystal fiber.

Lightning performance of transmission lines based upon real return-stroke current waveforms and statistical variation of characteristic parameters

This paper presents investigative studies concerning the lightning performance of 500kV transmission lines considering the characteristic parameters of first stroke current observed in measurement data along with its statistical variation. Therefore, advanced electromagnetic models were applied during the development of computational models, thus allowing a realistic representation of the first stroke current waveform. Lightning performance studies were conducted applying two of the most commonly used return-stroke current models, besides the first stroke current model recommended by CIGRÉ. The aim therefore is to identify which of these present the most accurate results, when compared to the use of real return-stroke current waveforms. The volt–time characteristics produced by each of the return-stroke current waveforms were evaluated using both the leader progression model (LPM) and volt–time curve. The breakdown process modelled through LPM is able to represent accurately the physical process established along the perimeter of the insulator strings, during a backflashover event. Analysis of leader length and velocity can reveal the influence of particular characteristics of lightning overvoltage waveform across the insulators produced by different return-stroke current waveforms in the assessment of the lightning performance of a transmission line. The computational modelling developed herein, allows identifying the critical current, the amplitude of the overvoltage that produces the backflashover, and the instant of time that breakdown occurs. The proposed modelling also makes it possible to determine in which insulator string and tower the backflash happens.

Fault diagnosis for large diesel fuel engine based on chaotic fractal method

In contrast with the large diesel engine fuel system operational condition complexity, the chaotic fractal characteristics in the combustion process of the diesel engine fuel system are systematically analyzed. Then, based on chaotic fractal method, an effective fault diagnosis method is further proposed. And under the two kinds of typical failure modes, the two important characteristic parameters variation trend for chaotic system, namely, correlation dimensions and the calculation methods of the maximum Lyapunov exponent are discussed. On the process of chaotic parameters calculation the wavelet noise reduction method is used to handle the original signal to conquer the linear scaling region properly. The results show that the maximum Lyapunov exponent method is a more effective method on the diesel engine fuel system fault diagnosis than the correlation dimension method, which can be further used in health condition assessment for this type fuel engine.

Advanced algorithms for cloud and modern information systems

Existing information systems are experiencing a bottleneck in dealing with complexity, dynamics, and uncertainties in their applications. After the technologies of integrated circuits, personal computers, and the Internet, Cloud computing is the latest information technology that is radically changing our daily life. With the fast development of cloud computing technology, various modern information network systems such as navigation system, fault Diagnosis system, indoor position system, resource management system, face detection system, and large-scale information system have achieved great advancement in recent years. The cloud and modern information systems should support data distribution, resource management, incomplete information processing, etc. This special issue brings together research articles covering advanced algorithms for cloud and modern information systems, including intelligent collision avoidance model for submarine in underwater navigation environment, fault diagnosis system for large diesel fuel engine, RFID-based three-dimensional (3D) indoor positioning system (IPS), QoS-aware mechanism in cloud, low-power mapping algorithm for 3D network on chip (NoC), new cascade classifier system for face detection, and improved genetic algorithm in the electroencephalographic (EEG)-based mental workload evaluation for miners. The papers in this special issue are arranged as follows. Yan-hua Liang and Chengtao Chen in the first paper ‘‘Intelligent Collision Avoidance based on 2D Risk model’’ proposed a novel and efficient collision risk model for handling with the challenging and imperative issue. The concepts of detection domain and fuzzy logic are adopted for modelling the degree of collision risk. The detection domain is used as the submarine safety scope when navigating under water, while the fuzzy logic is used as the mathematical implement for the analysis and synthesis of relations between obstacles or other submarines that are met in the navigation environment. The collision risk is regarded as one effective evaluation function that reflects which exact action should be done when the threshold of the risk degree is met. The second paper by Li et al. ‘‘Fault Diagnosis for Large Diesel Fuel Engine Based on Chaotic Fractal Method’’ investigates the chaotic fractal characteristics during the combustion process of the diesel engine fuel system to build an effective fault diagnosis method for large fuel engine based on chaotic fractal method. Considering the two kinds of typical failure modes, the two important characteristic parameters variation trend for chaotic system, namely, correlation dimensions, and the calculation methods of the maximum Lyapunov exponent are discussed. The results showed that the maximum Lyapunov exponent method is more proper to system fault detection. In the third paper ‘‘A Novel RFID ThreeDimensional Indoor Positioning System based on Trilateral Positioning Algorithm,’’ Xu et al. design and implement the RFID IPS based on received signal strength indicator (RSSI), which obtains 3D coordinates orientation through multiple trilateral positioning algorithm on location tag. RFID is the key component of the internet of things (IoT) and many fusion application systems combining RFID and cloud computing are emerging. The authors’ work in the IPS can deal with the problem that GPS system cannot provide indoor positioning services. Ye et al. in the fourth paper ‘‘A Novel QoS-Aware Mechanism for Provisioning of Virtual Machine Resource in Cloud’’ focus on efficient low-level resource provisioning and QoS guaranteed. A novel adaptive QoS-aware virtual machine provisioning mechanism is proposed to ensure efficient utilization of the system low-level resources. The VM for similar type of requests has been recycled so that the VM creation time can be minimized and used to serve more user requests. In the proposed model, QoS is linked by