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The purpose of this paper is to find an efficient way by using finite volume method (FVM) to simulate the aluminum alloy profile extrusion processes.

By assuming isotropic conditions, the hot aluminum material is described as a non‐linear Newtonian fluid material. Semi‐implicit method for pressure‐linked equations algorithm is used to calculate the physical fields, and the dynamic viscosity is updated then. Volume of fluid method and moving grid method are also used for unsteady flow to catch the free surface of the material and the moving bound.

FVM model in this paper is an accurate and efficient method for the numerical simulation of aluminum profile extrusion processes. Compared with finite element method software, FVM model is both memory and CPU efficient.

Provide theoretical reference for sound extrusion process and die designs, which are the key factors to produce desirable products in industrial production.

The paper finds an efficient way to introduce the FVM in computational fluid dynamics field into the simulation of the steady and unsteady aluminum alloy profile extrusion processes. It provides a reference for people who are interested in FVM and extrusion processes.

Nowadays, WiFi indoor positioning based on received signal strength (RSS) becomes a research hotspot due to its low cost and ease of deployment characteristics. To further improve the performance of WiFi indoor positioning based on RSS, this paper aims to propose a novel position estimation strategy which is called radius-based domain clustering (RDC). This domain clustering technology aims to avoid the issue of access point (AP) selection.

The proposed positioning approach uses each individual AP of all available APs to estimate the position of target point. Then, according to circular error probable, the authors search the decision domain which has the 50 per cent of the intermediate position estimates and minimize the radius of a circle via a RDC algorithm. The final estimate of the position of target point is obtained by averaging intermediate position estimates in the decision domain.

Experiments are conducted, and comparison between the different position estimation strategies demonstrates that the new method has a better location estimation accuracy and reliability.

Weighted k nearest neighbor approach and Naive Bayes Classifier method are two classic position estimation strategies for location determination using WiFi fingerprinting. Both of the two strategies are affected by AP selection strategies and inappropriate selection of APs may degrade positioning performance considerably.

The RDC positioning approach can improve the performance of WiFi indoor positioning, and the issue of AP selection and related drawbacks is avoided.

The RSS-based effective WiFi indoor positioning system can makes up for the indoor positioning weaknesses of global navigation satellite system. Many indoor location-based services can be encouraged with the effective and low-cost positioning technology.

A novel position estimation strategy is introduced to avoid the AP selection problem in RSS-based WiFi indoor positioning technology, and the domain clustering technology is proposed to obtain a better accuracy and reliability.

To develop electrode materials for supercapacitor with superior electrochemical performance and simple preparation process, the purpose of this study is to prepare flexible CC/NiS/a-NiS electrodes with self-supporting structure by loading hydrothermally synthesized a-NiS particles along with nano-NiS on carbon cloth by electroplating method.

The effects of current densities, temperatures and pH values on the loading amount and uniformity of the active substances during the plating process were investigated on the basis of optimization of surface morphology, crystalline structure and electrochemical evaluation as the cyclic voltammetry curves, constant current charge–discharge curves and AC impedance.

The a-NiS particles on CC/NiS/a-NiS were mostly covered by the plated nano-NiS, which behaved as a bulge and provided a larger specific surface area. The CC/NiS/a-NiS electrode prepared with the optimized parameter exhibited a specific capacitance of 115.13 F/g at a current density of 1 A/g and a Coulomb efficiency of 84% at 5 A/g, which is superior to that of CC/NiS electrode prepared by electroplating at a current density of 10 mA/cm², a temperature of 55°C and a pH of 4, demonstrating its fast charge response of the electrode and potential application in wearable electronics.

This study provides an integrated solution for the development of specifically structured NiS-based electrode for supercapacitor with simple process, low cost and high electrochemical charge/discharge performance, and the simple and easy-to-use method is also applicable to other electrochemically active composites.

The flexible eddy current array sensor has the characteristics of lightweight and flexibility, which has a great application prospect in the field of fatigue crack monitoring. But the exciting layout and feature signal extraction have a great influence on the crack monitoring characteristics of the sensor. This paper aims to propose a method using crack disturbed voltage as sensitivity to characterize crack propagation.

Flexible eddy current array sensors with reverse and codirectional exciting layout are proposed, and the advantages and disadvantages of three characterization methods based on the change of trans-impedance amplitude, the change of the trans-impedance’s real and imaginary part and the crack disturbed voltage are compared and analyzed by finite element simulation. Finally, the fatigue crack monitoring experiment is carried out.

The crack disturbed voltage and the change of trans-impedance’s imaginary part can effectively characterize the crack propagation for sensors with different exciting layouts. The codirectional exciting layout sensor has better crack identification sensitivity than the reverse exciting layout sensor, especially the induction coil 2. When the distance between the exciting coil and the induction coil is 0.1, 0.2 and 0.3 mm, it is increased by 372.09%, 295.24% and 231.43%, respectively.

Crack disturbed voltage can effectively characterize the crack propagation for sensors with two different exciting layouts.

Flexible eddy current array (FECA) sensor is flexible and light in weight, which has broad application prospects in structural health monitoring. But, the sensor’s sensing channel number is more, increasing the added mass of sensor networks. This paper aims to reduce the sensing channel number by changing the sensing coil layout.

In this paper, FECA sensors with series sensing coil (SSC) layout and interactive sensing coil (ISC) layout are proposed, which reduce the number of sensor’s channels by half. Then, the variation of the output signal of the sensor when the crack expands along both sides of the hole is analyzed by simulation model. Finally, the fatigue crack monitoring experiment is carried out.

For the SSC layout, the simulation results show that the amplitude of each SSC group of the sensor increases when the crack propagates to the left or right. For the ISC layout, when the crack propagates on the right side of bolt hole, the induced voltage of each ISC group decreases. When the crack propagates on the left side of bolt hole, the induced voltage of each ISC group increases. The experiment results are consistent with simulation results, which verifies the correctness of simulation model. Compared with SSC layout, the ISC layout can judge the crack propagation direction. And the crack monitoring accuracy is 1 mm.

The research results provide a certain reference for reducing the number of sensor’s sensing channels. Results of the simulation and experiment show that the ISC layout can judge the crack propagation direction, and the crack monitoring accuracy is 1 mm.

This paper aims to introduce the weighted squared Euclidean distance between points in signal space, to improve the performance of the Wi-Fi indoor positioning. Nowadays, the received signal strength-based Wi-Fi indoor positioning, a low-cost indoor positioning approach, has attracted a significant attention from both academia and industry.

The local principal gradient direction is introduced and used to define the weighting function and an average algorithm based on k-means algorithm is used to estimate the local principal gradient direction of each access point. Then, correlation distance is used in the new method to find the k nearest calibration points. The weighted squared Euclidean distance between the nearest calibration point and target point is calculated and used to estimate the position of target point.

Experiments are conducted and the results indicate that the proposed Wi-Fi indoor positioning approach considerably outperforms the weighted k nearest neighbor method. The new method also outperforms support vector regression and extreme learning machine algorithms in the absence of sufficient fingerprints.

Weighted k nearest neighbor approach, support vector regression algorithm and extreme learning machine algorithm are the three classic strategies for location determination using Wi-Fi fingerprinting. However, weighted k nearest neighbor suffers from dramatic performance degradation in the presence of multipath signal attenuation and environmental changes. More fingerprints are required for support vector regression algorithm to ensure the desirable performance; and labeling Wi-Fi fingerprints is labor-intensive. The performance of extreme learning machine algorithm may not be stable.

The new weighted squared Euclidean distance-based Wi-Fi indoor positioning strategy can improve the performance of Wi-Fi indoor positioning system.

The received signal strength-based effective Wi-Fi indoor positioning system can substitute for global positioning system that does not work indoors. This effective and low-cost positioning approach would be promising for many indoor-based location services.

A novel Wi-Fi indoor positioning strategy based on the weighted squared Euclidean distance is proposed in this paper to improve the performance of the Wi-Fi indoor positioning, and the local principal gradient direction is introduced and used to define the weighting function.

The purpose of this paper was to test the extract of barley as an environmentally friendly inhibitor for the acid corrosion of steel due to its wide availability as a popular major crop and its richness with different chemical constituents reported in literature (40) like alanine, glycine, serine, aspartic acid, leucine, valine, tyrosine and isoleucine with various number of functional groups that are able to chelate metal cations and to discuss the effect of temperature on its inhibition efficiency.

Electrochemical impedance spectroscopy (EIS) and polarization measurements were carried out using frequency response analyzer Gill AC instrument. The frequency range for EIS measurements was 0.1 ≤ f ≤ 1 × 103 with an applied potential signal amplitude of 10 mV around the rest potential. Polarization measurements were carried out at a scan rate of 30 mV/min, utilizing a three-electrode cell. A platinum sheet and saturated calomel electrode were used as counter and reference electrodes, respectively. The working electrode was constructed with steel specimens that have the following composition (weight per cent): C, 0.21; S, 0.04; Mn, 2.5; P, 0.04; Si, 0.35; and balance Fe.

Barley extract could act as an effective corrosion inhibitor for the acid corrosion of steel. The inhibiting action of the barley extract was attributed to its adsorption over the metal surface that blocks the available cathodic and anodic sites. Adsorption isotherms indicated that the adsorbed extract molecules cover one active center over the metal surface.

The research included the first use of an important world crop as an effective corrosion inhibitor that can reduce the corrosion of steel to an extent of 94 per cent.