Working Mode Research Articles

Investigation of a newly developed shear built-in valve type MR damper with high damping: Theories and experiments

Magnetorheological (MR) dampers are widely used as semi-active energy-dissipation devices in structural vibration control. Traditional MR dampers, particularly their working mode, often struggle to achieve a high damping force output and sometimes fail to meet the needs of practical engineering. Therefore, it is necessary to study MR dampers that can provide a high damping force. This study proposes an MR damper that combines a built-in shear valve with various working modes of shear extrusion. The damper generates a higher damping force by applying a current to the coils at different positions and altering its working mode. First, the ANSYS Maxwell software simulates the internal magnetic circuit of the damper to assess whether the magnetic field intensity distribution and circuit direction meet the design requirements. Analysis revealed that the internal magnetic circuit distribution was reasonable and satisfied the operating requirements of the damper. Furthermore, the mechanical models of the two working modes were derived based on the Bingham and double-viscous models. Finally, the accuracies of the mechanical models were verified experimentally. The experimental results showed that the simulation values closely matched the experimental values under all the working conditions. Therefore, the proposed mechanical models are reasonable, and can provide significant reference values for practical engineering applications.

Multi-manned disassembly line balancing problems for retired power batteries based on hyper-heuristic reinforcement

Considering the complexity and uncertainty of retired power batteries, worker disassembly can reduce the cost and increase the flexibility of the disassembly process. To address the problem of considerable waste products, we investigate a multi-manned disassembly line balancing problem with different work modes (MWM-DLBP). In addition, we explore the impact of variability in penalizing factors (earliness and tardiness) on costs when products of different scales need to be disassembled. Given the NP-hard of the problem and unpredictable situations, we propose a reinforcement learning-based Hyper-Heuristics (RLHHs) algorithm to solve the practical issues. A Markov model is constructed to generate a sequence of low-level metaheuristic algorithms, and a multi-armed bandit (MAB) method is designed to tune different critical parameters intelligently. The superiority of RLHHs is verified by comparing the optimization results with other algorithms. Further, results reveal that the new disassembly scheme can save an average cost of 9.81% compared to the original system design. Finally, we provide manufacturers with the specific workforce planning and working mode for disassembly tasks under different scenarios.

A high-sensitivity flexible piezoelectric tactile sensor utilizing an innovative rigid-in-soft structure

Piezoelectric tactile sensors are widely adopted to detect vibration and other stimuli. Among them, Polyvinylidene fluoride (PVDF) has the advantage of high flexibility, fast response and low cost. However, its sensitivity is restricted by the traditional d33 working mode. Herein, we proposed a rigid-in-soft structure with truncated pyramid shape and soft bottom layer to enhance the force-transmission efficiency. This design synergizes the d33 working mode and d31 working mode, thereby surpassing the sensitivity limit. The mechanism has been analyzed using Finite Element Modeling (FEM), and experiment results indicate that rigid-in-soft tactile sensor exhibits a sensitivity of 35.6 mV/N, along with a linear force detection range of 1–11 N. The sensitivity is approximately 1.7 times higher than that of control sensor without rigid pillar. Furthermore, the sensor displays a great flexibility and reliability, making it highly promising for detecting dynamic stimuli in robotics, such as slip and vibration.

Practical Considerations of Workplace Wellbeing Management under Post-Pandemic Work-from-Home Conditions.

As a natural experiment or "stress test" on the rapidly shifting work environment from office to home during and after the COVID-19 pandemic, staff wellbeing has been considered as the most critical issue in organizational change management. Following an overview of the relevant literature and recent official statistics, this essay aims to (i) address the major considerations and challenges in light of the transformation and re-design of the mode of work in the new normal and (ii) inform practical decisions for overall staff wellbeing under post-pandemic work-from-home (WFH) conditions with recommendations. For the sake of both staff healthiness and safety, as well as organizational competitiveness, senior management should take reasonable steps to enhance occupational safety in their WFH policy in line with practical recommendations on five areas, namely, (i) ergonomics, (ii) stress and anxiety management, (iii) workplace boundaries, (iv) work-family conflicts, and (v) other factors regarding a negative work atmosphere (e.g., loneliness attack, burnout, and workplace violence) particularly on virtual platforms. With the suggested evidence-based practices on WFH initiatives, senior management could make a difference in optimizing the overall workplace wellbeing of staff after the pandemic.

Multifunction Radar Working Mode Recognition With Unsupervised Hierarchical Modeling and Functional Semantics Embedding Based LSTM

Multifunction Radar Working Mode Recognition With Unsupervised Hierarchical Modeling and Functional Semantics Embedding Based LSTM

China in the era of ‘Top-level design’: hard steering by the central commission for comprehensively deepening reform (CCCDR) in National policymaking

This article reviews the history and working mode of the Central Commission for Comprehensively Deepening Reform (CCCDR) to shed light on the underpinnings of ‘top-level design’ in China’s policy process. We demonstrate the paradoxical nature of the CCCDR’s ‘hard steering’: on the one hand, agenda-setting and the creation of major reform policies has been centralized and highly formalized; on the other hand, local circumstances are not adequately taken into account, resulting in low resource-efficiency in policy implementation. This article makes an important contribution to our understanding of the Chinese policy process under conditions of ‘top-level design’. By showing how political steering is conducted at the central level and by drawing on a case study, we also critically assess the CCP’s governing capacity in the Xi Jinping era.

A Multi-Channel Data Simulator Based on the Time Unification System

In satellite and airborne electro-optical tracking systems, there are numerous processing devices and complex data flows. To ensure the coordinated operation of the system, the multiple devices within the target system must operate under unified time control for data acquisition, computation, and output. This study introduces a multi-channel data simulator based on a time unification system. The complete simulation system includes the host computer, simulator, target system, and time reference generator. The simulator has programmable input and output interfaces for multi-channel protocols and has storage and real-time working modes. In the storage mode, the simulated data are pre-transmitted to the simulator’s storage and sent to the target system according to the time reference generator. The simulator simultaneously stores the target system results. In the real-time mode, the host computer generates simulated data based on the target system’s results and outputs the data through the simulator in real time. The main contribution of the simulator is that it achieves system-level closed-loop simulation and completes the functional and performance verification of the target system. Through experimental verification, it is found that the simulator can achieve 4.2 Gbps of simulated data transmission and 1.6 Gbps of data reception and storage, with a closed-loop delay of 39.9 µs.

Investigation on the thermal performance of a dual driving force heat pipe under different working modes for thermal storage enhancement application

An embedded heat pipe (HP) with dual driving forces for compact and efficient thermal storage application was designed in this paper. To understand the thermal performance of the dual driving force heat pipe (DDFHP) under different heat storage and release conditions, an experiment testing platform was constructed. The influence of heating mode, heating load, and filling ratio (FR) on the working stability, thermal resistance, and effective thermal conductivity of the DDFHP were investigated and analyzed. The results mainly showed that under the bottom heating condition of the DDFHP, the thermal resistance of the DDFHP decreases with increasing heating power when the FR is low, and it first increases and then decreases when the FR is high. Among all the tested heating powers, the thermal resistance can be reduced to as low as 0.039 °C/W. Under the simulated heating conditions of phase change material on the DDFHP, at the same heating power, the thermal resistance of the DDFHP decreases first and then increases with the increase of the FR when the liquid filling height is less than 130 mm. In this case, the optimal FR of the DDFHP is 15 %, and the thermal resistance can be as low as 0.1 °C/W. The present study contributes to future HP applications in thermal storage enhancement.

AN EVALUATION METHOD OF AN ENERGY CONSUMPTION AS AN OPERATION PARAMETER IN A CYBER-PHYSICAL SYSTEM

The research of energy consumption in an Internet of Things network and its analytical evaluation is the goal of this work. The authors of this work concentrate on developing a model for calculating the actual gain in power consumption in order to estimate the actual energy required. The method suggests measuring the difference in energy usage under three primary battery-powered working modes to maximize a device's lifetime. Due to the fact that each CPS device state has its own energy metrics, it is feasible to choose the best operation course for entire network. The presented technique is certainly viable, as demonstrated by the experimental examination of Zigbee and BLE devices. The comparison of power levels using a temperature sensor in three basic scenarios (power modes) dictates how the CPS device lifetime can be optimized. Multi-regime consumption models, in which the rates of charging and discharging are dependent upon the energy level, are analyzed in this paper. This work aimed to state an optimal energy consumption by finding the right balance between operational power and battery lifetime through mathematical modeling. Therefore, it is easy to determine the energy cost of power stage, for instance, to send data by setting the minimal duration of each working condition in terms of power consumption. Moreover, a reasonable balance of power consumption and battery lifetime which impacts the data collection from sensors is vital to the development of data extraction algorithms. The practical results depict how device should be accessible to be able to lose less power even during switching on/off or how operate more effective if it used for a short period of time. A long-term network could become a reality once battery life is optimized enough to not disturb a user.

Design and Research of Intelligent Fixture for Drawing Machine

Tensile machine is a very sophisticated test equipment, which can test the mechanical properties of some materials. In the drawing machine, the clamping device is to prevent the relative displacement and vibration phenomenon in the process of tensile test. The clamping device is the most important part of the structure of the test machine, and the main task of the clamping device is to control the degree of freedom of the specimen needs to be clamped, so as to further add loads to the various specimens to be held, and finally complete the mechanical property test of the material. But at present, the existing fixture mechanism is mainly hydraulic, pneumatic, mechanical fixture. At present, the existing mechanical fixture still has bending stress during the clamping process, which will affect the accuracy of the experiment. Therefore, a clamping mechanism with adjustable clamping force and flat pushing is designed. An electric control type fixture mechanism is very rare, so in this paper, an electrically controlled fixture is designed on this basis. The main contents are as follows: (1) On the basis of the existing fixture types, the working mode of the fixture is studied, and the working principle related to the fixture is mastered. (2) The main components of the fixture mechanism are analysed, the design scheme is determined, and the selection of the components of the drive part and the selection of the related components within the fixture mechanism is completed. ( 3) The force analysis of the main body of the fixture is carried out by using theoretical mechanics knowledge, and the relevant calculations are completed. The solid modeling of the whole mechanism is completed by using SolidWorks. The force analysis of key parts is carried out by using ANSYS software, and the correctness and safety of material selection and design are verified. The main parts of the fixture mechanism to complete the corresponding force analysis, and the theoretical calculation results are compared and verified, and finally realize the electric control of the fixture mechanism and complete the design of the fixture mechanism.

Genetic algorithm-based path planning for grain leveling robot

Grain is the root of the people, and grain storage is a top priority. It is necessary to improve the efficiency of grain storage operations and reduce work intensity, so it is important to develop an automated or even intelligent grain leveling robot for the precise operation of grain silos. In this paper, we propose an area classification method based on target leveling height for the special working mode of truss-type grain leveling robot, simplify the 3D map to a 2D map, reduce the difficulty of path planning, and improve the working efficiency. Based on multi-level path planning and genetic algorithm to achieve the planning of the working path of the grain-leveling robot, it solves the problem of a large number of useless trips under the adoption of full-coverage operation. It saves a lot of time, improves grain-leveling efficiency, reduces energy consumption, optimizes the effect of grain-leveling, and helps realize the precise storage operation of grain silos. The experiment of rough leveling operation was carried out through the grain leveling robot prototype and the simulated experimental warehouse, and the results show that the height difference between the peak of the grain surface and the target leveling height is within 5 cm, which verifies that the path planning method in this paper is feasible, and shows that the grain leveling robot can complete the task of grain leveling and the effect is good.

Multi-degree-of-freedom ultra-low frequency vibration isolation system for precision devices with decoupled control

High precision devices are sensitive to low frequency background vibration. In order to meet the requirement of vibration isolation and adaptation to different working modes, a multi-DOF (Degree-of-Freedom) ultra-low frequency vibration isolation system is proposed. The system uses diaphragm bellow isolators to bear static load and electromagnetic actuators to exert control forces. Auxiliary isolators of variable stiffness are used to make the system adaptive to operation and transportation. The dynamic model of the vibration isolation system is established to analyze vibration characteristics and investigate control laws. A broadband control law based on the actuation-measurement state decoupling is proposed and the mixed feedback and feedforward control is adopted to realize ultra-low frequency vibration isolation. Numerical and experimental results have demonstrated that the proposed system is able to isolate ground vibration effectively. The initial vibration isolation frequency is reduced to 0.5 Hz and the transmissibility reaches −8.3 dB at 1 Hz and −21.9 dB at 2 Hz.

Academic ESP Courses in a Hybrid Mode: Attitudes and Perceptions

Developing academic ESP courses in a hybrid mode has come to the forefront of the educational agenda due to social and economic reasons: technological advance followed by the emergence of new communication, business and education technologies; new generations of learners who grow up in virtual reality rather than in real life; commercialisation of education; changes in workplaces and business organisations; a pandemic that resulted in increased use of the electronic and hybrid modes of interacting and working. In light of these circumstances, the research on the key actors in the educational process – learners and teachers – has gained importance and has become the reason to initiate a study of these actors’ attitudes and perceptions with regard to the academic ESP courses in a hybrid mode. The article presents and discusses the results from a survey conducted within this study and related to the preparation of reference criteria for course design in terms of parameters. Data analysis has implications for the educational sector in terms of language and subject course development, as well as of the introduction of relevant policies in higher education.

Real‐time estimation of the synchronous generator dynamic parameters using actual phasor measurement unit data and experimental evaluations

AbstractAn online non‐model‐based procedure is presented for estimating the synchronous generator (SG) dynamic parameters using practical phasor measurement unit (PMU) signals in the presence of uncertainty and noisy data. For this purpose, considering 8th‐order approximation, the SGs model is estimated in which, based on evaluating voltage and current phasors achieved from PMU data, dynamic parameters are estimated online. The proposed approach is a generalised concept of the Heffron–Philips model in which the variables and the gain factors are adaptable according to operating conditions. The proposed scheme is an online and non‐model‐based method in which the SG magnetic saturation behaviours are modelled through multivariable non‐linear definition to extend the accurate controlling structure. In this case, two different studies are carried out. In the first study, considering a single SG is connected to the infinite bus, the ability of the proposed method through simulation studies is evaluated. In the second study, the proposed scheme is developed practically in the laboratory whereby performing the experimental structure on different types through real‐time working mode, validation of the proposed estimated model through different operating points is evaluated. Experimental results show the effectiveness of the proposed practical scheme for estimating the generator's detailed model and non‐linear dynamic parameters through real‐time evaluations.

Working mode division and shift schedule extraction of a parallel hybrid power system

Abstract For hybrid electric vehicles, working mode division and shift schedule are two decisive factors affecting vehicle fuel economy. This paper introduces a method for vehicle working mode division and shift schedule determination on the basis of optimal system efficiency. The key index named ‘fuel-electricity conversion efficiency’ is defined and calculated. Via this method, unreasonable gear modes in specific working modes are excluded and the mode transition map and upshifting curves in each working mode are extracted. The simulation results demonstrate that, with the application of the single-motor multi-mode parallel hybrid power system, the proposed mode transition and shifting strategy can increase vehicle fuel economy by 12.99%.

Features of an Internal Communication Platform for Corporate Employees. Meeting the Needs of Employees in a Hybrid Era

Abstract More and more corporations are adopting a hybrid work style in which employees can work both at the office and at home. The popularity of the hybrid workplace is a result of the Covid-19 pandemic crisis and one of the components of the hybrid work mode is the internal organizational communication platform without which the hybrid work mode could not exist However, internal platforms for corporate online organizational communication are not tailored to the needs of employees. Thus, this study outlines the characteristics that an internal communication platform between employees of a corporation must have to meet their needs. To find out which characteristics are important for the employees of a corporation, adequate data has been collected using a Kano questionnaire distributed online and analysed with the Kano quantitative method. The main result of the research is that the characteristics of the communication platform between employees must focus on meeting their psychological needs (e.g., the need for socialization, for recognition, to be motivated, etc.). The present paper provides a new perspective on how to communicate in organizations, focusing on the psychological needs of corporate employees since in the new hybrid era, meeting these needs with the help of online organizational communication is more important than technical attributes.

Electric vehicle charger energy management by considering several sources and equalizing battery charging

This article proposes a novel energy management structure for electric vehicles, consisting of a supercapacitor and two types of batteries, to improve efficiency and navigable distance. The key features of a suitable energy storage system include high power and energy density, low cost and weight, minimal maintenance, and long life. Although batteries are the primary power storage source in electric vehicles, they have power limitations. Therefore, a high-power-density supercapacitor is added to the battery to create a hybrid energy storage system, reducing stress on the battery and increasing its lifespan. The article presents a new structure for hybrid storage systems based on the existence of a main battery, a replaceable battery, a supercapacitor, and a DC-DC converter. An active charge equalizer circuit for the main battery in standby mode and its control system are also introduced. A control method for dividing power between different sources under different conditions is presented, and the design parameters of the energy storage system are optimized using a genetic algorithm to minimize mass and losses. The performance of the proposed system is evaluated through simulation in MATLAB software and tested in a small-scale laboratory sample. The article also provides a detailed analysis of different working modes, including electric motor acceleration, low-speed mode, high-speed mode, and electric regenerative braking mode. Additionally, a control method for energy management between batteries and supercapacitors is introduced, aiming to increase efficiency. The results show that the proposed hybrid energy storage system can effectively improve the efficiency of electric vehicles.

Evolution and Implications During the Epidemic-Contemplation on the Robust Communities amid the Group Purchase Trend amid the Shanghai Outbreak

In March 2020, Shanghai experienced an outbreak of an epidemic and implemented several months of territory-wide static management. The community was the smallest closure and control unit for grid control. This thesis uses questionnaire interviews, literature review, and correlation analysis to study the phenomenon of community chiefs and regimentation during the Shanghai outbreak, taking the Shannan Estate in Shanghai as an example. This paper reports that the headman model has improved the mechanism and mode of grassroots work, tapped elite talents, and established a mechanism of community self-organisation and multi-party participation oriented to the needs of residents in the social aspect. In the spatial aspect, the construction of a five-minute community living circle was combined with the improvement of the mechanism of composite use of community facilities. This statement will have a positive impact on strengthening community resilience and promoting sustainable development in the post-epidemic era.

Evolution and Implications During the Epidemic-Contemplation on the Robust Communities amid the Group Purchase Trend amid the Shanghai Outbreak

In March 2020, Shanghai experienced an outbreak of an epidemic and implemented several months of territory-wide static management. The community was the smallest closure and control unit for grid control. This thesis uses questionnaire interviews, literature review, and correlation analysis to study the phenomenon of community chiefs and regimentation during the Shanghai outbreak, taking the Shannan Estate in Shanghai as an example. This paper reports that the headman model has improved the mechanism and mode of grassroots work, tapped elite talents, and established a mechanism of community self-organisation and multi-party participation oriented to the needs of residents in the social aspect. In the spatial aspect, the construction of a five-minute community living circle was combined with the improvement of the mechanism of composite use of community facilities. This statement will have a positive impact on strengthening community resilience and promoting sustainable development in the post-epidemic era.

ANALYSIS OF THE REQUIREMENTS FOR DATA ANALYST AND DATA SCIENTIST POSITIONS IN THE LABOR MARKET

The labour market in the field of data analytics was analysed in this article. Specifically, there were analysed the requirements for vacancies Data Analyst and Data Scientist. The analysis covered such job search platforms as Work.ua (Ukraine), Robota.ua (Ukraine), DOU (Ukraine), Djinni (Ukraine), The Muse (USA), Technojobs (France), Careerjet (Canada), Profesia (Czech Republic, Slovakia), Reed (UK). The study was consisted of 4 stages: semi-automated data collection, processing of key job requirements, data storage and structuring, and data analysis. Such tools as Python (streamlit, pandas, re) and AirTable were used in the study. The structure and style of job postings on job search sites were analysed. Patterns were discovered that could be used to derive key indicators. Algorithms for replacing missing data, such as work experience, were discovered. An application was developed to automate the process of analysing of the text of vacancies. The user interface was implemented using the Streamlit framework. A total of 1000 vacancies were collected for analysis. Of these, 586 were collected from Ukrainian sources, and the rest were from abroad. The research was based on the analysis of the following indicators: the frequency of vacancies by position (junior, middle, senior); the type of companies looking for Data Analyst or Data Scientist; the mode of work (offline, online and hybrid); the level of English proficiency; visualisation tools that the candidate should know; preferred programming language; desired database; requirements for office tools; requirements for knowledge of specialised libraries for data analysis and machine learning. All these indicators were quantitatively analysed and a conclusion was drawn. A table, that clearly demonstrates the researched trends, have been developed by authors.