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The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

This paper aims to investigate the problem of estimating the angle of attack (AoA) and relative velocity for vertical axis wind turbine (VAWT) blades from computational fluid dynamics data.

Two methods are implemented as function objects within the OpenFOAM framework for estimating the blade’s AoA and relative velocity. For the numerical analysis of the flow around and through the VAWT, 2 D unsteady Reynolds-averaged Navier–Stokes (URANS) simulations are carried out and validated against experimental data.

To gain a better understanding of the complex flow features encountered by VAWT blades, the determination of the AoA is crucial. Relying on the geometrically-derived AoA may lead to wrong conclusions about blade aerodynamics.

This study can lead to the development of more robust optimization techniques for enhancing the variable-pitch control mechanism of VAWT blades and improving low-order models based on the blade element momentum theory.

Assessment of the reliability of AoA and relative velocity estimation methods for VAWT’ blades at low-Reynolds numbers using URANS turbulence models in the context of dynamic stall and blade–vortex interactions.

To improve the speed and accuracy of turbine blade film cooling design process, the most advanced deep learning models were introduced into this study to investigate the most suitable define for prediction work. This paper aims to create a generative surrogate model that can be applied on multi-objective optimization problems.

The latest backbone in the field of computer vision (Swin-Transformer, 2021) was introduced and improved as the surrogate function for prediction of the multi-physics field distribution (film cooling effectiveness, pressure, density and velocity). The basic samples were generated by Latin hypercube sampling method and the numerical method adopt for the calculation was validated experimentally at first. The training and testing samples were calculated at experimental conditions. At last, the surrogate model predicted results were verified by experiment in a linear cascade.

The results indicated that comparing with the Multi-Scale Pix2Pix Model, the Swin-Transformer U-Net model presented higher accuracy and computing speed on the prediction of contour results. The computation time for each step of the Swin-Transformer U-Net model is one-third of the original model, especially in the case of multi-physics field prediction. The correlation index reached more than 99.2% and the first-order error was lower than 0.3% for multi-physics field. The predictions of the data-driven surrogate model are consistent with the predictions of the computational fluid dynamics results, and both are very close to the experimental results. The application of the Swin-Transformer model on enlarging the different structure samples will reduce the cost of numerical calculations as well as experiments.

The number of U-Net layers and sample scales has a proper relationship according to equation (8). Too many layers of U-Net will lead to unnecessary nonlinear variation, whereas too few layers will lead to insufficient feature extraction. In the case of Swin-Transformer U-Net model, incorrect number of U-Net layer will reduce the prediction accuracy. The multi-scale Pix2Pix model owns higher accuracy in predicting a single physical field, but the calculation speed is too slow. The Swin-Transformer model is fast in prediction and training (nearly three times faster than multi Pix2Pix model), but the predicted contours have more noise. The neural network predicted results and numerical calculations are consistent with the experimental distribution.

This paper creates a generative surrogate model that can be applied on multi-objective optimization problems. The generative adversarial networks using new backbone is chosen to adjust the output from single contour to multi-physics fields, which will generate more results simultaneously than traditional surrogate models and reduce the time-cost. And it is more applicable to multi-objective spatial optimization algorithms. The Swin-Transformer surrogate model is three times faster to computation speed than the Multi Pix2Pix model. In the prediction results of multi-physics fields, the prediction results of the Swin-Transformer model are more accurate.

Gillette’s historically successful “razor and blade” business model (RBM) has been a promising benchmark for multiple businesses across diverse industries worldwide in the past several decades. The extant literature deals with very few nuances of this business model notwithstanding the fact that there are several variants of this business model being put to practical use by firms in diverse industries in grossly metaphorically equivalent situations.

This study adopts the 2 × 2 truth table framework from the domains of mathematical logic and combinatorics in fleshing out all possible (four logical possibilities) variants of the razor and blade business model for further analysis. This application presents four mutually exclusive yet collectively exhaustive possibilities on any chosen dimension. Two major dimensions (viz., provision of subsidy and intra- or extra-firm involvement in the making of razors or blades or both) form part of the discussion in this paper. In addition, this study synthesizes and streamlines entrepreneurial wisdom from multiple intra-industry and inter-industry benchmarks in terms of real-time firms explicitly or implicitly adopting several variants of the RBM that suit their unique context and idiosyncratic trajectory of evolution in situations that are grossly reflective of the metaphorically equivalent scenario of razor and recurrent blades. Inductive method of research is carried out with real-time cases from diverse industries with a pivotally common pattern of razor and blade model in some form or the other.

Several new variants of the razor and blade model (much beyond what the extant literature explicitly projects) have been discovered from the multiple metaphorically equivalent cases of RBM across industries. All of these expand the portfolio of options that relevant entrepreneurial firms can explore and exploit the best possible option chosen from them, given their unique context and idiosyncratic trajectory of growth.

This study has enriched the literature by presenting and analyzing a more inclusive or perhaps comprehensive palette of explicit choices in the form of several variants of the RBM for the relevant entrepreneurial firms to choose from. Future research can undertake the task of comparing these variants of RBM with those of upcoming servitization business models such as guaranteed availability, subscription and performance-based contracting and exploring the prospects of diverse combinations.

Smart entrepreneurial firms identify and adopt inspiring benchmarks (like razor and blade model whenever appropriate) duly tweaked and blended into a gestalt benchmark for optimal profits and attractive market shares. They target diverse market segments for tied-goods with different variants or combinations of the relevant benchmarks in the form of variegated customer value propositions (CVPs) that have unique and enticing appeal to the respective market segments.

Value-sensitive customers on the rise globally choose the option that best suits them from among multiple alternatives offered by competing firms in the market. As long as the ratio of utility to price of such an offer is among the highest, even a no-frills CVP may be most appealing to one market segment while a plush CVP may be tempting to yet another market segment simultaneously. While professional business firms embrace resource leverage practices consciously, amateur customers do so subconsciously. Each party subliminally desires to have the maximum bang-to-buck ratio as the optimal return on investment, given their priorities ceteris paribus.

Prior studies on the RBM have explicitly captured only a few variants of the razor and blade model. This study is perhaps the first of its kind that ferrets out many other variants (more than ten) of the razor and blade model with due simplification and exemplification, justification and demystification.

The purpose of this paper aims to design a robust wind turbine emulator (WTE) based on a three-phase induction motor (3PIM).

The 3PIM is driven by a soft voltage source inverter (VSI) controlled by a specific space vector modulation. By adjusting the appropriate vector sequence selection, the desired VSI output voltage allows a real wind turbine speed emulation in the laboratory, taking into account the wind profile, static and dynamic behaviors and parametric variations for theoretical and then experimental analysis. A Mexican hat profile and a sinusoidal profile are therefore used as the wind speed system input to highlight the electrical, mechanical and electromagnetic system response.

The simulation results, based on relative error data, show that the proposed reactive power control method effectively estimates the flux and the rotor time constant, thus ensuring an accurate trajectory tracking of the wind speed for the wind emulation application.

The proposed architecture achieves its results through the use of mathematical theory and WTE topology combine with an online adaptive estimator and Lyapunov stability adaptation control methods. These approaches are particularly relevant for low-cost or low-power alternative current (AC) motor drives in the field of renewable energy emulation. It has the advantage of eliminating the need for expensive and unreliable position transducers, thereby increasing the emulator drive life. A comparative analysis was also carried out to highlight the online adaptive estimator fast response time and accuracy.

The purpose of this study is to develop a straightforward method for creating a non – toxic metal oxide sensor capable of detecting melamine in milk at ambient temperature.

A low temperature, straightforward solution-based approach, specifically the hydrothermal method was utilized to apply the active sensing layer onto the substrate. Subsequently, analysis of the cyclic voltammetry (CV) profile was conducted to detect the concentration of melamine and determine its sensitivity.

An experimental analysis was performed on a nontoxic metal oxide-based sensor fabricated for detecting melamine sensitivity using the CV profile. The sensor’s performance was evaluated under three different concentrations of melamine (0.1 mmol, 0.2 mmol and 0.3 mmol). The results demonstrated a satisfactory sensitivity of 0.0297 µAmM⁻¹cm⁻² with a response time of 2 s.

The primary innovation of this research lies in the creation of a nontoxic and environmentally friendly sensor. The synthesis method employed featured significantly lower temperatures compared to existing literatures. Furthermore, the sensor achieved enhanced sensitivity along with rapid response times.

Focusing on the social influence processes in the context of massively multiplayer online role-playing games (MMORPGs), this study aims to investigate the nomological network of social influence factors, a topic seldom explicitly articulated in the literature in this unique context.

This study adopts a mixed-methods approach to develop and test a context-specific model of social influence processes in MMORPGs. First, the authors conducted qualitative interviews with MMORPG players to identify the drivers shaping players' perceptions of social influences. Second, the authors formulated and tested a research model with quantitative data collected from 450 respondents of an online survey.

Through the qualitative study, the authors identify leader enthusiasm, social support and social presence as the critical drivers of social influence factors. The result of the quantitative study validates the influences of the critical drivers and demonstrates the impact of social influences on MMORPG players' we-intention to continue playing games.

This research extends the social influence theory by identifying contextualized drivers that shape MMORPG players' perception of social influences determining their we-intention to continue playing games. MMORPG service providers can draw on these drivers to leverage social influences to increase players' we-intention of continuance.

The research focused on analysing a unique type of heat exchanger that uses swirling air flow over heated tubes. This heat exchanger includes a round baffle plate with holes and opposite-oriented trapezoidal air deflectors attached at different angles. The deflectors are spaced at various distances, and the tubes are arranged in a circular pattern while maintaining a constant heat flux.

This setup is housed inside a circular duct with airflow in the longitudinal direction. The study examined the impact of different inclination angles and pitch ratios on the performance of the heat exchanger within a specific range of Reynolds numbers.

The findings revealed that the angle of inclination significantly affected the flow velocity, with higher angles resulting in increased velocity. The heat transfer performance was best at lower inclination angles and pitch ratios. Flow resistance decreased with increasing angle of inclination and pitch ratio.

The average thermal enhancement factor decreased with higher inclination angles, with the maximum value observed as 0.94 at a pitch ratio of 1 at an angle of 30°.

Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.

The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.

To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.

This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

This paper aims to present a low-cost, edge-fed, windmill-shaped, notch-band eliminator, circular monopole antenna which is practically loaded with a complementary split ring resonator (CSRR) in the middle of the radiating conductor and also uses a partial ground to obtain wide-band performance.

To compensate for the reduced value of gain and reflection coefficient because of the full (complete) ground plane at the bottom of the substrate, the antenna is further loaded with a partial ground and a CSRR. The reduction in the length of ground near the feed line improves the impedance bandwidth, and introduced CSRR results in improved gain with an additional resonance spike. This results in a peak gain 3.895dBi at the designed frequency 2.45 GHz. The extending of three arms in the circular patch not only led to an increase of peak gain by 4.044dBi but also eliminated the notch band and improved the fractional bandwidth 1.65–2.92 GHz.

The work reports a –10dB bandwidth from 1.63 GHz to 2.91 GHz, which covers traditional coverage applications and new specific uses applications such as narrow LTE bands for future internet of things (NB-IoT) machine-to-machine communications 1.8/1.9/2.1/2.3/2.5/2.6 GHz, industry, automation and business-critical cases (2.1/2.3/2.6 GHz), industrial, society and medical applications such as Wi-MAX (3.5 GHz), Wi-Fi3 (2.45 GHz), GSM (1.9 GHz), public safety band, Bluetooth (2.40–2.485 GHz), Zigbee (2.40–2.48Ghz), industrial scientific medical (ISM) band (2.4–2.5 GHz), WCDMA (1.9, 2.1 GHz), 3 G (2.1 GHz), 4 G LTE (2.1–2.5 GHz) and other personal communication services applications. The estimated RLC electrical equivalent circuit is also presented at the end.

Because of full coverage of Bluetooth, Zigbee, WiFi3 and ISM band, the proposed fabricated antenna is suitable for low power, low data rate and wireless/wired short-range IoT-enabled medical applications.

The antenna is fabricated on a piece (66.4 mm × 66.4 mm × 1.6 mm) of low-cost low profile FR-4 epoxy substrate (0.54 λ_g × 0.54 λ_g) with a dielectric constant of 4.4, a loss tangent of 0.02 and a thickness of 1.6 mm. The antenna reflection coefficient, impedance and VSWR are tested on the Keysight technology (N9917A) vector network analyzer, and the radiation pattern is measured in an anechoic chamber.