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A novel concept is proposed in the present study for improving the square-array jet impingement heat transfer by integrating a synthetic jet actuator into the array unit. To illustrate the potential of this concept, an experimental investigation is performed, wherein two jet Reynolds numbers (Re = 3000 and 5000), three hole-to-hole pitches (X/d = Y/d = 4, 5 and 6), and three impinging distances (H/d =2,6 and 10) are considered while the synthetic jet is actuated at a fixed frequency of 180 Hz with a characteristic Reynolds number (Re0) of about 2430. The results show that the synthetic jet has rare influence on the stagnation heat transfer of square-array jet but effectively improves the local heat transfer at the central zone of array unit. Its potential is tightly dependent on the array layout, Reynolds number and impinging distance. In general, the spatially-averaged Nusselt number augment behaves more significantly for the situations with smaller jet Reynolds number and bigger impinging distance. [ABSTRACT FROM AUTHOR]

During electrochemical discharge drilling (ECDD), tool electrode bending and debris accumulation easily lead to secondary discharges and instability, which will affect the removal of recast layers. To improve the stability and processing quality of the machining process, a novel vibration-assisted electrochemical discharge drilling (VAECDD) method has been proposed. In this method, vertical vibrations are applied to the workpiece, causing pulsating fluctuations in the pressure and velocity of the working fluid, thereby carrying away the debris. This ensures adequate and uniform electrochemical reactions to remove the recast layer. The simulation and experiments were carried out with different vibration frequencies and amplitudes. The simulation results show the vibration frequency has a more obvious influence on the transient pressure. The experiment shows that the machining accuracy, efficiency, and the removal effect of recast layers all show an upward trend with the increase of vibration frequency, while first increasing and then decreasing with the increase of vibration amplitude. When the vibration frequency and amplitude are 40 kHz, 0.7 μm, the removal rates of recast layers are above 97%. It is an effective machining approach for high-quality, accurate, and efficient of film cooling holes. [ABSTRACT FROM AUTHOR]

This paper proposes using a WiFi-based identification system, Wi-ID, to identify users from their unique hand gestures. Hand gestures from the popular game rock-paper-scissors are utilized for the system's user authentication commands. The whole feature of three hand gestures is extracted instead of the single gesture feature extracted by the existing methods. Dynamic time warping (DTW) is utilized to analyze the amplitude information in the time domain based on linear discriminant analysis (LDA), while extract amplitude kurtosis (AP-KU) and shape skewness (SP-SK) are utilized to analyze the Wi-Fi signals energy distribution in the frequency domain. Based on the contributions of the extracted features, the random forests algorithm is utilized for weight inputs in the long short-term memory (LSTM) network. The experiment is conducted on a computer installed with an Intel 5300 wireless networking card to evaluate the effectiveness and robustness of the Wi-ID system. The experiment results showed the accuracy of the proposed Wi-ID system has a personal differentiation accuracy rate over 92%, and with an average accuracy of 96%. Authorized persons who performed incomplete hand gestures are identified with an accuracy of 92% and hostile intruders can be identified with a probability of 90%. Such performance demonstrates that the Wi-ID system achieved the aim of user authentication. [ABSTRACT FROM AUTHOR]

Learning-based multi-view stereo (MVS) methods have demonstrated promising results. However, very few existing networks explicitly take the pixel-wise visibility into consideration, resulting in erroneous cost aggregation from occluded pixels. In this paper, we explicitly infer and integrate the pixel-wise occlusion information in the MVS network via the matching uncertainty estimation. The pair-wise uncertainty map is jointly inferred with the pair-wise depth map, which is further used as weighting guidance during the multi-view cost volume fusion. As such, the adverse influence of occluded pixels is suppressed in the cost fusion. The proposed framework Vis-MVSNet significantly improves depth accuracy in reconstruction scenes with severe occlusion. Extensive experiments are performed on DTU, BlendedMVS, Tanks and Temples and ETH3D datasets to justify the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]

Mineral hydrogels have caught a lot of attention for their strong competency as artificial skin-like materials. Nonetheless, it remains a great difficulty in fulfilling in one hydrogel system a range of key functionalities that are needed for practical artificial skin applications, i.e., to be biocompatible, strain-sensitive, ion-conductive, elastic and robust, anti-swelling, and anti-freezing. Here we present a such type of versatile hydrogel that is not only capable to deliver all the above-mentioned key functionalities but also highly stable. This novel hydrogel is constructed by introducing a gelatinous and amorphous multi-ionic biomineral (denoted as Mg-ACCP, containing Mg2+, Ca2+, CO32−, and PO43−) into the network of biocompatible polyvinyl alcohol (PVA) and sodium alginate (SA). The presence of Mg2+ and PO43− in this hydrogel helps prohibit the crystallization of the biominerals, leading to significantly improved stability. The hydrogel thus obtained delivers excellent mechanical performance due to the chelation between the mineral ions and the organic matrix, and high sensitivity even to subtle pressure and strain applied, such as slight finger bending and gentle tapping. Furthermore, the novel hydrogel features high ionic conductivity, high resistance to swelling, and extraordinary anti-freezing property, holding great promise for applications in different practical scenarios, particularly in aqueous or cold environments. [ABSTRACT FROM AUTHOR]

The application of sustainable manufacturing technologies is the new challenge faced by enterprises, industries, and researchers under the background of supporting carbon peak and carbon neutral. This paper studies how to reduce the energy consumption of hole machining through optimizing tool path and cutting parameters simultaneously. The integrated optimization methodology can further reduce the energy consumption comparing with optimizing the tool path or cutting parameters separately. Firstly, the energy model of hole machining is established based on machine tools' energy composition, tool path planning, and process parameters. Due to the fact that tool path planning as air cutting process has big relationship with reducing energy, especially for hole group with a big proportion, the tool path of hole processing is optimized by the improved ant colony algorithm to solve the issue considering the distance from one hole to the next hole. Based on this optimized path, a multi-objective optimization model for one hole cutting parameters is established, considering the spindle speed and feed rate as the optimization variables and machining time, energy consumption, and surface roughness as the objective function. The non-dominated sorting genetic algorithm (NSGA-II) is employed to solve the multi-objective optimization problem of hole machining. Finally, the case study with 50 holes is used to testify the application of the proposed method to provide the practical energy efficiency strategy for hole group or multi-hole parts on CNC machines assisting in achieving sustainable production in manufacturing sectors. [ABSTRACT FROM AUTHOR]

There is a variety of schemes when a part with multiple features is processed in CNC machines, and hence, different feature sequencing and cutting parameter selections affect not only productivity but also energy consumption. This paper concentrates on the energy-saving strategy by optimizing the feature processing sequence and machining parameters in the part processing stage through reducing the energy consumption of the non-cutting and cutting process respectively. Firstly, the energy consumption of the cutting of parts is established using unit volume cutting energy (SEC) on cutting volume, while the normal feed and the rapid feed are established in different moving axes, respectively. Meanwhile, the detailed energy model is established considering rapid feed and general feed path in the X, Y, Z + , Z − directions for analyzing the impact of feature sorting on reducing the energy consumption of non-cutting. The non-cutting energy consumption model is established involving automatic tool change, ordinary feed, and fast feed factors. Based on the developed model, the multi-objective optimization of cutting energy consumption, machining quality, and machining time is carried out by NSGA-II algorithm, and the path optimization of empty cutting energy consumption is carried out by genetic algorithm. Finally, a cutting orthogonal experiment is executed to collect energy consumption data, analyze the data, and fit the data to establish a specific energy consumption model for each processing stage. A case study of a part with eight features is used to optimize sequencing and parameters, which shows the effectiveness and validity of the proposed method. [ABSTRACT FROM AUTHOR]

The main goal of this study is to create a robust control system that could guide or replace pilots in the tracking of the commanded velocity and attitude in multimodal maneuver, while complex dynamics and uncertain aerodynamic cross-coupling among control surfaces of compound helicopter are considered. To this end, a Pi-Sigma neural network (PSNN) adaptive controller is proposed based upon the certainty-equivalence (CE) principle, where a novel Lyapunov-based weight self-tuning algorithm augmented with e-modification is designed to realize efficient uncertainty approximation and guarantee robustness of convergence process. Compared with traditional neural networks in control field, stronger generalization ability of PSNN must be balanced against weaker stability, which leads to inevitable parameters perturbation. Therefore, an incremental nonlinear dynamic inversion (INDI) framework is established to decouple original overactuated system and reject parameters perturbation in PSNN. Meanwhile, by incorporating Lagrange multiplier method into allocation, an original incremental allocation method is designed to get globally ideal control input according to time-varying working capability of each surface. In terms of Lyapunov theorem, it is demonstrated that the closed-loop augmented system driven by the proposed control scheme is semi-global uniformly ultimately bounded. Finally, by comparing with existing methods, the simulation validates the effectiveness of proposed control scheme. [ABSTRACT FROM AUTHOR]

For improving energy efficiency of machining process, extensive studies focused on how to establish energy consumption model and optimize cutting parameters. However, the existing methods lack a systematic method to promote the widespread use of energy efficiency methods in industry. This paper proposes a systematic method integrating energy model, experiment design, and multi-objective optimization model. Firstly, the energy model is established considering cutting energy and non-cutting energy. Then, the orthogonal experiment is designed with the three levels of four factors of spindle speed, feed speed, cutting depth, and cutting width in the X and Y cutting directions. The data of energy consumption, surface quality, and machining time are obtained to study the effects of different cutting elements and cutting directions. Meanwhile, the standby, spindle idling, feed, SEC (specific energy consumption), material cutting, and idling feed models of the CNC machine tools are established based on the experimental data. Additionally, five sets of experimental data are tested for verifying the accuracy of the established energy consumption model, which can reach 99.4%. Finally, a multi-objective optimization model for high efficiency and energy saving of processing process is established to optimize the cutting parameters considering energy consumption, processing time, and surface quality simultaneously. Combining the case of milling with constraints including machine tool performance, tool life, processing procedures, and processing requirements, the Pareto solution set is used to solve the Pareto of the target model. Through drawing a three-dimensional needle graph and two-dimensional histogram, the optimal cutting parameter combination for rough machining and semi-finish machining is provided assisting in promoting the application of the sustainable techniques in the industry. [ABSTRACT FROM AUTHOR]

A waste corn cob core-derived SiO2 @ graphene-like carbon nanocomposite (CCC) has been synthesized by a hydro-thermal and high-temperature carbonization process. The CCC material is carbonized at 900 °C (CCC-900). The SiO2 nanoparticle with a granule size of 100–200 nm could be grown on the graphene-like carbon nanosheets. The BET-specific surface area can be calculated to be 481.81 m2 g−1. When it is used as an anode material for lithium-ion battery, the CCC composite can display the foremost discharge capacity of 2051.5 mAh g−1 at 200 mA g−1 and the maintain capacity of 125 mAh g−1 after 200 cycles. The high foremost discharge capacity could be attributed to the synergistic effect of SiO2 nanoparticles and graphene-like sheets. [ABSTRACT FROM AUTHOR]

Engine nozzle orifices are broadly used in the automotive field, and their manufacture entails high drilling accuracy, consistency, and excellent machined surface quality. Electrochemical discharge drilling (ECDD) is an innovative compound machining technique, which can be used to machine small holes of difficult-to-cut materials. Electrical discharge machining (EDM) as well as electrochemical machining (ECM) can occur simultaneously in ECDD, owing to which it can obtain not only good surface quality but also high processing speed. However, the machining accuracy, taper, and surface quality achieved using ECDD do not satisfy the requirements of engine nozzle orifices, which are of a higher standard. For improving the machining accuracy and surface quality, a variable-parameter electrochemical discharge drilling (VPECDD) has been proposed. The machining process is divided into two consecutive stages, including perforation and shape modification, while different parameters are used in different stages. In this study, the finite element method was applied to study the mechanism of VPECDD, and comparative experiments were performed among EDM, ECDD, and VPECDD. The results indicate that VPECDD can achieve very high machining accuracy and consistency, obtain an inlet and outlet diameter difference at 0.002 mm, maintain an average hole taper at 0.0004°, and remove the recast layer completely. Finally, it is verified that VPECDD is suitable for machining microholes with high precision and no recast layer. [ABSTRACT FROM AUTHOR]

Recently, tissue engineering has developed into a powerful tool for repairing and reconstructing damaged tissues and organs. Tissue engineering scaffolds play a vital role in tissue engineering, as they not only provide structural support for targeted cells but also serve as templates that guide tissue regeneration and control the tissue structure. Over the past few years, owing to unique physicochemical properties and excellent biocompatibility, various types of two-dimensional (2D) nanomaterials have been developed as candidates for the construction of tissue engineering scaffolds, enabling remarkable achievements in bone repair, wound healing, neural regeneration, and cardiac tissue engineering. These efforts have significantly advanced the development of tissue engineering. In this review, we summarize the latest advancements in the application of 2D nanomaterials in tissue engineering. First, each typical 2D nanomaterial is introduced briefly, followed by a detailed description of its applications in tissue engineering. Finally, the existing challenges and prospects for the future of the application of 2D nanomaterials in tissue engineering are discussed. [ABSTRACT FROM AUTHOR]

In this work we report a facile route to grow large area, uniform, continuous and few-layer α-In2Te3 film via chemical vapor deposition (CVD) methods. The characterizations show the large area of CVD-grown few-layer α-In2Te3. This method guarantees the precise control of thickness down to few layers and large area preparation. The magnetoresistance (MR) properties of few-layer In2Te3 was investigated from 2 to 300 K and its MR stability under long exposure to ambient air was studied for the first time. Few-layer of α-In2Te3 shows a positive MR and the largest transverse MR was observed to about 11% at 2 K and a high stability of MR to long time exposure in air up to 21 weeks. [ABSTRACT FROM AUTHOR]

The rapid development of the Internet of vehicles and the sudden urban traffic conditions bring increasing load pressure on the ground communication network. To solve this problem, in this paper we propose a joint and dynamic routing approach for connected vehicles in Low Earth Orbit (LEO) constellation satellite networks. Firstly, to realize global path planning service, the global situational awareness is conducted by jointing the satellite to transferee the acquired data to the control center which makes the initial route then. We employ the shortest-path algorithm and the ant colony optimization to jointly obtains the optimal end-to-end multi-hop path of the transmission. The joint and dynamic routing scheme in LEO network makes up for the shortcoming of ground communications. Simulation results show that the proposed routing method for connected vehicle networks in this paper is feasible and promising. [ABSTRACT FROM AUTHOR]