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Due to existence of skin effect under rotational excitation, especially to high-frequency motors and power transformers run at the frequency of hundreds or even thousands of hertz, core losses will increase significantly, which may cause local overheating damage, and the efficiency and longevity will be decreased. The purpose of this paper is to accurately calculate the rotational anomalous loss in electrical steel sheets.

The influence of skin effect to rotational anomalous loss coefficient is described in detail. Based on the rotational core losses calculation approach, the transformed coefficient and parameters of rotational anomalous loss are determined in accordance with experimental data obtained by using 3D magnetic properties testing system. Then, a variable loss coefficient calculation model of rotational anomalous loss is built. Meanwhile, a separation of the total 2D elliptical rotation experimental core losses is worked out.

The two methods are analysed and compared qualitatively. It should be noted that the novel calculation model can be more effectively presented anomalous loss features. Moreover, quantitative comparisons between 2D elliptical rotation and alternating core losses have achieved beneficial conclusions.

Transformed rotational anomalous loss coefficient and parameters of electrical steel sheets considering skin effect are determined. Based on that, a novel calculation model evaluating 2D elliptical rotation anomalous loss is presented and verified based on the experimental measurement and the separation of the total 2D elliptical rotation core losses. The 2D elliptical rotation core losses separation method and quantitative comparison with alternating excitation are helpful to engineering application.

This study aims to provide a better understanding of the market balance between regular (high-carbon) and green (low-carbon) products. Further, this study analyses the role of government subsidy policy, based on the results of the government’s optimal green subsidy decision and its implication for green market segmentation and social welfare.

This study adopts a Stackelberg game framework to study the interaction between the government’s subsidy regulations and the firms’ marketing regimes. When considering government subsidy decision, we use multi-objective programming theory and turn the problem into weighted single-objective optimisation programming.

This study explores three marketing regimes and identifies the conditions under which each regime should be adopted by a firm. Further, investigating the optimal subsidy decision problem for the government reveals three subsidy regimes corresponding to the three marketing regimes. The government may be stuck in a regime of useless subsidy and the reason for this phenomenon is analysed as well.

Developing the model into a more complex supply chain situation will enhance the applicability of the framework. Incorporating other environmental regulations, such as carbon tax, can be interesting research extensions of this study.

This study provides a quantitative framework, which can help the regulator gain a deeper understanding of green subsidy policies and assist focal companies in acquiring a better appreciation of green marketing segmentation.

The study is one of the first few works to explore the optimal design of green subsidy regulation for the government and its impact on market segmentations of high- and low-carbon products by using quantitative modelling approaches and deriving vital managerial insights.

This paper aims to propose and establish a set of new benchmark models to investigate and confidently validate the modeling and prediction of total stray-field loss inside magnetic and non-magnetic components under harmonics-direct current (HDC) hybrid excitations. As a new member-set (P21^e) of the testing electromagnetic analysis methods Problem 21 Family, the focus is on efficient analysis methods and accurate material property modeling under complex excitations.

This P21^e-based benchmarking covers the design of new benchmark models with magnetic flux compensation, the establishment of a new benchmark measurement system with HDC hybrid excitation, the formulation of the testing program (such as defined Cases I–V) and the measurement and prediction of material properties under HDC hybrid excitations, to test electromagnetic analysis methods and finite element (FE) computation models and investigate the electromagnetic behavior of typical magnetic and electromagnetic shields in electrical equipment.

The updated Problem 21 Family (V.2021) can now be used to investigate and validate the total power loss and the different shielding performance of magnetic and electromagnetic shields under various HDC hybrid excitations, including the different spatial distributions of the same excitation parameters. The new member-set (P21^e) with magnetic flux compensation can experimentally determine the total power loss inside the load-component, which helps to validate the numerical modeling and simulation with confidence. The additional iron loss inside the laminated sheets caused by the magnetic flux normal to the laminations must be correctly modeled and predicted during the design and analysis. It is also observed that the magnetic properties (B27R090) measured in the rolling and transverse directions with different direct current (DC) biasing magnetic field are quite different from each other.

The future benchmarking target is to study the effects of stronger HDC hybrid excitations on the internal loss behavior and the microstructure of magnetic load components.

This paper proposes a new extension of Problem 21 Family (1993–2021) with the upgraded excitation, involving multi-harmonics and DC bias. The alternating current (AC) and DC excitation can be applied at the two sides of the model’s load-component to avoid the adverse impact on the AC and DC power supply and investigate the effect of different AC and DC hybrid patterns on the total loss inside the load-component. The overall effectiveness of numerical modeling and simulation is highlighted and achieved via combining the efficient electromagnetic analysis methods and solvers, the reliable material property modeling and prediction under complex excitations and the precise FE computation model using partition processing. The outcome of this project will be beneficial to large-scale and high-performance numerical modeling.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

Digital transformation is a confidence booster in intrapreneurship, but few have examined its impact on intrapreneurship. Further, quantitative analyses exploring the impact of Chinese enterprises' digital transformation on intrapreneurship at the micro-level are rare. Most enterprises do not have the dividend for digital transformation, and few enterprises have successfully achieved digital transformation through intrapreneurship, internal management re-engineering and technological innovation. This study investigates the effect of digital transformation on intrapreneurship in Chinese real economy enterprises.

The study develops and tests a theoretical model that digital transformation impacts intrapreneurship by promoting working capital turnover and furtherly influencing labor input. Panel data of 1,638 Chinese-listed companies between 2007 and 2020 were used to complete the empirical test.

Digital transformation impacted labor input, with an inverted-U shaped relationship between the two, and labor input significantly stimulated intrapreneurship. This effect promoted labor input's impact on working capital. Chinese real economy enterprises generally increase labor investment to promote intrapreneurship. Heterogeneity analysis revealed that enterprises' asset scale and ownership attributes uniformly affected labor input.

This study provided empirical evidence of the promotional effect of real economy enterprises' digital transformation on intrapreneurship. Further, it advanced the literature by examining this relationship at the micro-level. Moreover, the data sample was long-term and included most industries, thus providing representative results with practical implications.

The advantages of blockchain technology are being widely discussed by academics, the business community and government, because blockchain can promote data sharing, optimise business processes, reduce operation costs, improve collaborative efficiency and build credible systems. The supply chain is becoming a key area for the application of blockchain technology. However, few studies have discussed the effect of such emerging technologies on the supply chain in depth. Therefore, this paper aims to analyse how blockchain empowers supply chain and promotes supply chain management.

Based on a review of relevant literature and blockchain applications in practice, this paper analyses the development and research status of blockchain technologies. In addition, considering the different operational processes within the supply chain, the authors discuss the opportunities and challenges of blockchain technologies, such as the transparency of supply, intelligent manufacturing, the security of logistics, the platformisation of sales and the ecology of governance.

The authors find that information sharing, information traceability and trust establishment are the key categories of research achievements and applications of supply chain management. The central issues for blockchain researchers are the authenticity of transaction data, the traceability of long supply chains and the establishment of trust for all participants.

From the practical and theoretical perspectives, this paper shows the development of blockchain technologies to clarify the challenges, opportunities and prospects. This paper elucidates and facilitates the development of emerging interdisciplinary research and the practice of supply chain.

In rotational alternating current machines, interlocking is a commonly used manufacturing method to fix laminated silicon steel cores. The purpose of this study is to measure the localized magnetic properties more comprehensively and to analyze the deteriorated magnetic properties caused by interlocking more accurately.

A movable B–H sensor is designed in this paper. The localized magnetic properties measurement was performed to investigate the magnetic properties around the interlocks with various sizes, various orientations and various numbers of laminations. Then, the damaged area caused by the interlocking was quantified, and the magnetic degradation of different degrees is layered.

The measurement results have shown that the interlocks with larger sizes, along the transverse direction and on 10-layer laminate, will lead to more serious magnetic degradation, and the maximum loss increment can reach up to 70%.

This work is an improvement and optimization based on the previous overall magnetic measurement of the interlock. The quantitative results of the localized magnetic measurement will have a certain significance for the accurate modeling and simulation of the electrical machines and provide valuable guidance for the optimization of the actual production process of the motor.

The purpose of this study is to investigate the effect of punching on the local magnetic properties of the nonoriented electrical steel sheet.

A microcomposite B–H sensor consisting of a pair of B probes with a spacing of 2 mm and a 1.8 × 1.8 mm² H coil is designed. The region and degree of local magnetic properties degradation caused by punching can be quantitatively analyzed by flexibly moving the composite B–H sensor. The influence and physical mechanism of punching on the hysteresis loss, eddy current loss and excess loss are analyzed based on the Bertotti loss separation theory.

This study investigates the deterioration effect of the punched nonoriented electrical steel. The permeability near the edge decreases, and the core loss as well as the microhardness increases. The region of magnetic property deterioration is dependent on the area of work hardening.

The microcomposite B–H sensor can be used to measure the magnetic properties near the edge of electrical steel sheets under different processing conditions. This study provides the possibility of precise magnetic property model of the motor core after punching, especially valuable for motors without annealing process.

This paper aims to investigate the influence of the contact status between the seal ring and its support on the seal performance in hydrostatic mechanical face seal.

A thermal fluid-solid interaction (TFSI) model of hydrostatic mechanical face seal is further developed, in which the multi-body contacts between components are particularly given more attention. The numerical models of the flow field and complete seal assemblies are developed. A specific energy equation is obtained to simplify the calculation of film temperature. Based on the mechanism for the continuity condition of the physical quantities at the fluid–solid interface, the TFSI model uses an on-line iterative coupling method.

The contact status between seal ring and its support affects the seal performance significantly. The rotating ring and the stationary ring contribute differently because of the contact status difference.

The contact status between the seal ring and the ring seat is key to gain an insight into the performance of the hydrostatic mechanical face seal thus provides guidance for mechanical seal design.