Search results

Induction heating as an energy source is a novel, recent method in extrusion-based metal additive manufacturing. The purpose of this paper is to develop an optimized coil for extrusion-based metal wire additive manufacturing. The optimized coil is so designed that uniform temperature distribution can be achieved in the extruder, achieving uniform material deposition in a semi-solid state, which is required for additive manufacturing.

Coil shape optimization is achieved by using arrangement of coil turns as a control variable in the form optimization process, and the objective function is to minimize the gradient in the distribution of the magnetic field to achieve uniform heating in the extruder for maintaining consistent solid and liquid fraction during material deposition. A combination of numerical solutions and geometrical optimization has been used for this study.

Experimental and simulation results reveal that the optimized induction coil produced a more uniform axial temperature distribution in the extruder, which is suitable for maintaining a uniform solid-to-liquid fraction ratio during material deposition.

The author has investigated the use of optimized-shaped induction coils in extrusion-based additive manufacturing. The optimized coil can achieve a more uniform temperature distribution in the extruder in comparison to the standard helical coil used in the existing process, which means optimized coil achieves a more uniform solid-to-liquid ratio during printing in comparison to existing standard coil shapes used for heating extruders and fulfils the requirement of additive manufacturing.

The aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.

Fuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.

Digital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.

This study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

Drawn from the push–pull perspective, this research aims to identify the determinants of Chinese technology's outward foreign direct investments (OFDI) into the Eurasian region.

The authors argue that contrary to the extant literature, technology-driven OFDI from emerging-market multinationals (EMNEs) do not always seek developed countries, and EMNEs' technology investments in emerging economies are rising indicating that there are factors in these economies that can prove attractive. The authors recognize the influence of the macroeconomic environment and the interaction of home and host-country institutional contexts that influence the location choice of EMNEs technology-driven OFDI into other emerging economies, mediated by the industry sector and firm's ownership structure. The authors test our hypotheses using a sample of 1,656 observations of Chinese MNEs' tech-investments in the Eurasian region from 2005 to 2019.

The study results indicate that bilateral diplomatic relations pave the way of the host-country institutional environment for Chinese MNEs uncovering the role of the Chinese government as an OFDI facilitator. This study also unveils a lower technology level of the Chinese MNEs' investments in the Eurasian region connoting an interest in market opportunities exploitation through their existing technologies – through its comparative advantage in the global markets – rather than strategic assets acquisition aiming at augmenting their technological capabilities. This trend is similar to that of other major foreign direct investment (FDI) source countries.

This research contributes to a better understanding of the characteristics and the location choice of technology investments from EMNEs into other emerging economies that have received scant attention in the literature. In addition, it extends the institutional theory by analyzing how home-country institutions, through bilateral diplomatic relations, may smooth the host country institutional environment for home-country MNEs' foreign investments and contributes as well to the debate on the applicability of the existing theoretical framework in the case of emerging-market MNEs.

Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.