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Topology optimization is a state-of-the-art technique for the innovative design of electromagnetic devices. The ON/OFF method is a typical approach for this purpose. However, the drawbacks of long iteration time and poor ability to express curved surfaces make the industry not shown their due interest so far in the ON/OFF method. The purpose of this paper is to study a novel ON/OFF method for topology optimization, which can bring feasible optimized shapes that are more friendly for industrial realization in a shorter time.

The proposed improved ON/OFF method uses structured triangular elements for finite element modeling because the triangular elements can more freely express shape features. Every four triangular elements are pieced together to form a square cell, each quadrilateral cell is associated with a binary value indicating the material state of the four triangular elements. The binary metaheuristic algorithms are used to optimize the material distribution. After the material filling for the elements based on the output of the metaheuristic algorithm, a two-step surface smoother will be performed as the postprocess to make the shapes more friendly for manufacturing.

The comparative numerical results on a benchmark topology optimization problem show that the proposed method can bring feasible optimized shapes that are more friendly for industrial realization in a shorter time. In addition, the speed and robustness of convergence, especially in the case of multiobjective topology optimization problem, are significantly improved.

A novel ON/OFF method for topology optimization is proposed. Compared with the traditional ON/OFF method, the proposed method is better in terms of searching efficiency and robustness. Moreover, the proposed method can provide feasible optimized shapes that are more friendly for industrial realization.

Topology optimization (TO) methods have shown their unique advantage in the innovative design of electric machines. However, when introducing the TO method to the rotor design of interior permanent magnet (PM) synchronous machines (IPMSMs), the layout parameters of the magnet cannot be synchronously optimized with the topology of the air barrier; the full design potential, thus, cannot be unlocked. The purpose of this paper is to develop a novel method in which the layout parameters PMs and the topology of air barriers can be optimized simultaneously for aiding the innovative design of IPMSMs.

This paper presents a simultaneous TO and parameter optimization (PO) method that is applicable to the innovative design of IPMSMs. In this method, the mesh deformation technique is introduced to make it possible to make a connection between the TO and PO, and the multimodal optimization problem can thereby be solved more efficiently because good topological features are inherited during iterative optimization.

The numerical results of two case studies show that the proposed method can find better Pareto fronts than the traditional TO method within comparable time-consuming. As the optimal design result, novel rotor structures with better torque profiles and higher reluctance torque are respectively found.

A method that can simultaneously optimize the topology and parameter variables for the design of IPMSMs is proposed. The numerical results show that the proposed method is useful and practical for the conceptual and innovative design of IPMSMs because it can automatically explore optimal rotor structures from the full design space without relying on the experience and knowledge of the engineer.

In this paper, the authors study the effect of consumers' fairness preferences on dynamic pricing strategies adopted by platforms in a non-cooperative game.

This study applies fair game and repeated game theory.

This study reveals that, in a one-shot game, if consumers have fairness preferences, dynamic prices will slightly decline. In a repeated game, dynamic prices will be reduced even when consumers do not have fairness preferences. When fairness preferences and repeated game are considered simultaneously, dynamic prices are most likely to be set at fair prices. The authors also discuss the effect of platforms' discounting factors, the consumers' income and alternative choices of consumption on the dynamic prices.

The study findings illustrate the importance of incorporating behavioral elements in understanding and designing the dynamic pricing strategies for platforms and the implications on social welfare in general.

The authors developed a theoretical model to incorporate consumers' fairness preference into the decision-making process of platforms when they design the dynamic pricing strategies.

The purpose of this paper is to present a practical and efficient iterative method for predicting vehicle-induced response of bridge.

The vehicle-bridge interaction (VBI) problem is generalized mathematically and a computational algorithm for VBI is proposed. This method rests on an iterative procedure, which utilizes the whole interaction process for iteration. By this means, vehicle and bridge become totally uncoupled and are only linked by the contact force history. This method provides flexibility to choose simplified or refined vehicle and bridge models for the VBI problem, as well as open options for different commercial FEM software without specialized codes.

The method is verified through two numerical examples. The first example uses a simple 1D beam bridge model, which illustrates the procedure of this method and demonstrates its fast convergence in several iterations. The second example employs a realistic full 3D finite element bridge model, which shows that the method easily connects complex FEM bridge models in ABAQUS with a calibrated vehicle model in Matlab. The dynamic response of the bridge is reliably calculated within only a few iterations.

The proposed iterative method separates vehicle and bridge into independent subsystems in the computational process, thus providing more flexibility to utilize commercial FEM softwares. Its efficiency is realized through choosing the whole interaction force process for iteration, which considerably reduces the iteration steps.

This paper aims to enhance the reliability of self-validating multifunctional sensors.

An effective fault detection, isolation and data recovery (FDIR) strategy by using kernel principal component analysis (KPCA) coupled with gray bootstrap and fault reconstruction methods.

The proposed FDIR strategy is able to the address fault detection, isolation and data recovery problem of self-validating multifunctional sensors efficiently.

A KPCA-based model which can overcome the limitation of existing linear-based models is used to achieve the fault detection task. By using gray bootstrap method, the position of all faulty sensitive units can be calculated even under the multiple faults situation. A reconstruction-based contribution method is adopted to evaluate the amplitudes of the fault signals, and the fault-free output of the faulty sensitive units can be used to replace the fault output.

Rural residential energy consumption accounts for 46.6% of total building-related energy consumption of China. In Northeast China, energy consumption for space heating represents a significant proportion of total rural residential energy consumption and has reached 100 million tce (tons of standard coal equivalent), or more than 60% of total household energy consumption. In terms of energy consumption per square meter of gross floor area, rural residential energy consumption for heating is more than that of cities (20kgce/m2). However, the average indoor temperature of most rural residence is below 10°C, much less than that in cities (18°C). Hence, it is an important task for Chinese energy saving and emission reduction to reduce rural residential energy consumption, while enhancing indoor thermal comfort at the same time.

Restricted by local technology and low economic level, rural residences currently have poor thermal insulation resulting in severe heat loss. This paper reports on research aimed at developing design strategies for improving thermal insulation properties of rural residences with appropriate technology. A field survey was conducted in six counties in severe cold areas of Northeast China, addressing the aspects of indoor and outdoor temperature, humidity, internal and external surface temperature of building envelop enclosure, and so on.

The survey data show the following:

1. Modern (after 2000) brick-cement rural residences perform much better than the traditional adobe clay houses and Tatou houses (a regional type of rural residence in Northeast China – see figure A) in overall thermal performance and indoor thermal comfort;

2. Among the traditional residential house types, adobe clay houses have better heat stability and thermal storage capacity than Tatou houses;

3. Applying an internal or external thermal insulation layer can greatly improve rural residential thermal insulation properties, and is an economical and efficient solution in rural areas;

4. In terms of roofing materials, tiled roofs show much better thermal insulation properties than thatch roofs;

5. Adopting passive solar techniques can form a transition space (greenhouse) against frigid temperatures, resulting in interior temperatures 5.91°C higher than the outside surroundings. It is evident that local passive solar room design offers significant heat preservation effects and lower cost ($12/m2), embodies the ecological wisdom of rural residents, and is therefore important to popularize.

The above experimental results can provide guidance in energy conservation design for both self-built residences and rural residences designed by architects. In addition, the results can also provide experimental data for energy-saving studies for rural residences in China.

The purpose of this paper is to quickly manufacture full Cu₃Sn-microporous copper composite joints for high-temperature power electronics applications and study the microstructure evolution and the shear strength of Cu₃Sn at different bonding times.

In this paper, a novel structure of Cu/composite solder sheet/Cu was designed. The composite solder sheet was made of microporous copper filled with Sn. The composite joint was bonded by thermo-compression bonding under pressure of 0.6 MPa at 300°C. The microstructure evolution and the growth behavior of Cu₃Sn at different bonding times were observed by electron microscope and metallographic microscope. The shear strength of the joint was measured by shear machine.

At initial bonding stage the copper atoms in the substrate and the copper atoms in the microporous copper dissolved into the liquid Sn. Then the scallop-liked Cu₆Sn₅ phases formed at the interface of liquid Sn/microporous copper and liquid Sn/Cu substrates. During the liquid Sn changing to Cu₆Sn₅ phases, Cu₃Sn phases formed and grew at the interface of Cu₆Sn₅/Cu substrates and Cu₆Sn₅/microporous copper. After that the Cu₃Sn phases continued to grow and the Cu₃Sn-microporous copper composite joint with a thickness of 100 µm was successfully obtained. The growth rule of Cu₃Sn was parabolic growth. The shear strength of the composite joints was about 155 MPa.

This paper presents a novel full Cu₃Sn-microporous copper composite joint with high shear strength for high-temperature applications based on transient liquid phase bonding. The microstructure evolution and the growth behavior of Cu₃Sn in the composite joints were studied. The shear strength and the fracture mechanism of the composite joints were studied.

This chapter derives sentiment indicators (implied volatility and implied skewness) from the option pricing models of Corrado and Su (1996), Bakshi, Kapadia, and Madan (2003), and Zhang, Zhen, Sun, and Zhao (2017), and then integrates these sentiment indicators with artificial intelligence deep neural network (AIDNN) for developing the behavioral finance AIDNN (BFAIDNN) algorithms. We apply the BFAIDNN algorithms to daily derivatives data of Taiwan Futures and Options markets from 2015 to 2017. Our results demonstrate that the trading strategies established by the BFAIDNN algorithms can generate positive rewards.

The purpose of this paper is to employ a Yin-Yang harmony perspective to propose a novel circled 5C model to understand the unique harmonizing process of how conflicts are resolved in China. Despite increasing research on labor conflicts in Chinese manufacturing, Western theories still can not explain how Chinese culture influences conflict management.

The authors investigate a large manufacturer where a severe labor strike happened in South China. A mixed-methods research design is adopted. The scale of Chinese harmony and analysis of variance are used to identify the underlying unharmonious factors triggering the labor strike. The grounding theory approach (a case study) was adopted to further examine the proposed 5C model.

“Harmony with corporate system”, “Harmony between departments” and “Harmony with firm leader” were found to arouse employee grievances the most. Differences in age, gender, marital status, educational level, tenure and position were discovered to affect workers’ perceptions of workplace harmony. The proposed 5C model was supported.

As a lesson in handling escalating labor conflicts, this study allows foreign investors to better understand how to cope with relevant labor strife issues in China. In addition, this project integrates research with consultancy service, which can be seen as an exciting step forward in bridging academics and practitioners.

Based on Yin-Yang harmony thinking, this study suggests an integrative, context-specific concern – concern for harmony for China to transcend the Western dual-concern model regarding the choice of coping with conflicts. The paper constructs a novel circled 5C model of the Chinese harmonizing process (conflict, clash, communication, comprise and consensus), which characterizes the dynamic, contingent and art-oriented nature of Chinese conflict management.