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The purpose of this paper is to propose a quasi-three-dimensional (3D) thermohydrodynamic (THD) model for oil film bearings with non-Newtonian and temperature-viscosity effects. Its performance factors, including precision and time consumption, are investigated.

Two-dimensional (2D), 3D and quasi-3D numerical models are built. The thermal and mechanical behaviors of two types of oil film bearings are simulated. All the results are compared with solutions of commercial ANSYS CFX.

The 2D THD model fails to predict the temperature and pressure field. The results of the quasi-3D THD model coincide well with those of the 3D THD model and CFX at any condition. Compared with the 3D THD model, the quasi-3D THD model can greatly reduce the CPU time consumption, especially at a high rotational speed.

This quasi-3D THD model is proposed in this paper for the first time. Transient mechanical and thermal analyses of high-speed rotor-bearing system are widely conducted using the traditional 3D THD model; however, the process is very time-consuming. The quasi-3D THD model can be an excellent alternative with high precision and fast simulation speed.

In general, the existing compressor design methods require abundant knowledge and inspiration. The purpose of this study is to identify an intellectual design optimization method that enables a machine to learn how to design it.

The airfoil design process was solved using the reinforcement learning (RL) method. An intellectual method based on a modified deep deterministic policy gradient (DDPG) algorithm was implemented. The new method was applied to agents to learn the design policy under dynamic constraints. The agents explored the design space with the help of a surrogate model and airfoil parameterization.

The agents successfully learned to design the airfoils. The loss coefficients of a controlled diffusion airfoil improved by 1.25% and 3.23% in the two- and four-dimensional design spaces, respectively. The agents successfully learned to design under various constraints. Additionally, the modified DDPG method was compared with a genetic algorithm optimizer, verifying that the former was one to two orders of magnitude faster in policy searching. The NACA65 airfoil was redesigned to verify the generalization.

It is feasible to consider the compressor design as an RL problem. Trained agents can determine and record the design policy and adapt it to different initiations and dynamic constraints. More intelligence is demonstrated than when traditional optimization methods are used. This methodology represents a new, small step toward the intelligent design of compressors.

This paper aims to predict the 28-day compressive strength of recycled thermal insulation concrete more accurately.

The initial weights and thresholds of BP neural network are improved by genetic algorithm on MATLAB 2014 a platform.

Genetic algorithm–back propagation (GA-BP) neural network is more stable. The generalization performance of the complex is better.

The GA-BP neural network based on the training sample data can better realize the strength prediction of recycled aggregate thermal insulation concrete and reduce the complex orthogonal experimental process. GA-BP neural network is more stable. The generalization performance of the complex is better.

The purpose of this paper is to investigate the electrodeposition of copper coatings directly onto AZ31 magnesium alloy, considered as a substrate of electroplating nickel. The additive, pH, complexing agent, current density, time, and temperature of electrolytic bath were studied to understand electrodepositing copper coating on AZ31 magnesium alloy.

Electrodeposition of copper was carried out in an aqueous solution containing copper hydroxide, citrate, and fluorine ion, which avoids the replacement or corrosion of the magnesium alloy. The morphology, structure, and interface of the electrodeposited copper coating were investigated by a scanning electron microscope (SEM).

The copper coating was dense, and there was good adhesion of the copper coating on the AZ31 magnesium alloy. This suggests that successful deposition of copper using an electroplating process could decrease the cost of coating AZ31 magnesium alloy.

This paper will be helpful for the development of coating on magnesium alloy using electroplating processes.

Copper hydroxide and citrate were the main compositions of the electrolyte, combined with sodium poly dipropyl (SP) and polyethylene glycol (PEG) as brightening agents and can be used to electrodeposit copper directly onto AZ31 magnesium alloy.

Extant research on supply chain integration defines integration in different ways, and mainly discusses a limited number of integration elements. The purpose of this paper is to develop a conceptual integration model which consists of comprehensive elements that are important to academic research and industrial practices.

Key literature survey with drawing threads of existing practices together for developing a systematic referential model and then verify the model with a real case.

Developed a model consisting of integration elements residing at the strategic, managerial, operational, and fundamental levels (bottom line). Based on the benefit alignment, the total integration requires supply chain partners to integrate resource flows (material, information, knowledge, and finance), processes and organization, planning and control activities and strategy.

The research is based on secondary data and a case study illustration. Further empirical research is required.

The normative model can guide managers to integrate resources and activities in their efforts for an effective supply chain management. It supplements the Supply Chain Operations Reference Model developed by the Supply Chain Council with an interface description, which may guide the development of information systems for supply chain integration.

The comprehensive model provides a more inclusive and integrated perspective of supply chain integration. It is expected that the consensus of supply chain integration could be achievable based on this model. The conceptual framework will assist the researchers to determine integration variables of supply chain.

This study explores the influencing factors of smart supply chain innovation (SSCI) for going global companies and designs a theoretical framework.

This paper is a multi-case study that includes a combination of exploratory and explanatory case studies.

First, the authors find that SSCI is embodied in product development and supply chain empowerment, which represent exploitative innovation and explorative innovation, respectively. Meanwhile, supply chain empowerment has a positive impact on product development. Second, the going global policy affects the transformation of supply chain empowerment to SSCI practices. Third, in terms of exploitative innovation, personalized demand positively affects SSCI through product development. Finally, explorative innovation, including emerging technology application and supply chain ecologicalization, has a positive effect on supply chain empowerment and thereby affects SSCI.

Supply chain innovation in the context of a smart economy has gained great popularity. This study sheds light on the influencing factors and mechanisms of SSCI from the exploitative and explorative aspects of innovations.

In this study, the authors examined demand-side credit in rural China with the aims of understanding attribute preferences and the willingness of farmers to pay for credit.

The authors implemented an in-the-field discrete choice experiment (DCE) using a D-optimal block (6 × 9 × 3) design applied to 420 farm households across five Chinese provinces (Shandong, Sichuan, Shaanxi, Jiangsu and Henan) in the summer and fall of 2018. The DCE included six attributes including the interest rate, term of loan, type of loan, type of repayment, type of institution and mobile banking services.

Conditional and mixed logit results indicated a downward sloping credit demand curve with variable elasticity across regions. Provincial willingness-to-pay (WTP) indicators suggested that farmers were willing to pay a premium for long-term ( 0.03–0.687%) and low collateral credit loans ( 0.79–2.93%). Also, four of five provinces indicated a preference for loan amortization rather than lump-sum payment. Interestingly, in comparison to the Agricultural Bank of China (ABC), only farmers in Shandong, Sichuan and Shaanxi indicated a preference for rural credit cooperatives (RCCs)/banks and the Postal Savings Bank of China (PSBC). Another quite surprising result was bank services, in our case, access to mobile banking did not appear to induce WTP for agricultural credit. While conditional and mixed logit regression coefficients were similar (and therefore robust), the authors found that there was substantial heterogeneity across attribute preferences on term of loan, type of loan and amortization. Preferences for type of lender and mobile banking were generally homogenous. This result alone suggested that lenders should consider offering a suite of credit products with different attributes in order to maximize the potential pool of borrowers. While there were some differences across provinces, farmers appeared to be indifferent to lenders, and it did not appear that offering banking services such as mobile banking had any bearing on credit decisions.

This paper presents a first step in using in-the-field choice experiments to better understand rural finance in China. Although the sample size satisfies conventional levels of significance and rank conditions, the authors caution against attributing results to China as a whole. Different provinces have different institutional structures and agricultural growing conditions and economies and these effects may differentially affect WTP for credit. Although by all indications farmers were aware of credit, not all farmers, in fact a minority, actually borrowed from a financial institution. This is not unusual in China, but for these farmers, the DCE was posed as hypothetical. Likewise, the study’s design was based on a generic credit product typical of rural China, and the authors caution against making inferences about other products with different attributes and risk structures.

This study is motivated by the rapidly changing dynamic in China's agricultural economy. With specific reference to new laws and regulations about the transfer of land use rights (LURs), China's agricultural economy is undergoing significant and rapid change which will require better understanding by policy makers, lenders and practitioners of the changing credit needs of farmers, including the new and emerging class of commercial farmers.

To the best of the authors’ knowledge, the authors believe that the result provided in this paper present the first use of in-the-field DCE and are the first to be reported in either the English or Chinese literature on rural credit product design.

Describes a non‐contact optical sensing technology called C3D that is based on speckle texture projection photogrammetry. C3D has been applied to capturing all‐round 3D models of the human body of high dimensional accuracy and photorealistic appearance. The essential strengths and limitation of the C3D approach are presented and the basic principles of this stereo‐imaging approach are outlined, from image capture and basic 3D model construction to multi‐view capture and all‐round 3D model integration. A number of law enforcement, medical and commercial applications are described briefly including prisoner 3D face models, maxillofacial and orofacial cleft assessment, breast imaging and foot scanning. Ongoing research in real‐time capture and processing, and model construction from naturally illuminated image sources is also outlined.

This study investigates the existence of Marshall, Jacob and Porter’s type of externalities in Mexico. We measure the impact of industrial specialization, competition and diversity on employment growth for the period 2004 to 2008.

The analysis is based on data from 41 highly dynamic industrial clusters originally obtained by applying Porter’s (1998) methodology. We use a cross-section specification estimated via instrumental variables and two-stage least square estimation (2SLS) to control for endogeneity.

On average, we find that industrial specialization exerts a negative impact on employment growth within states and within clusters, indicating that traded industries in Mexico carry very little innovation, operate in early stages of the life cycle, face high costs of employment reassignation or exhibit low adaptability. A negative impact of specialization on employment conforms with Jacobs (1969) type of externalities and confirms what other studies have found in France (Combes, 2000), Korea (Lee et al., 2005) and the USA (Delgado et al., 2014). The authors also find that competition generates more employment.

Industrial data at the sub-branch level were obtained from the Economic Census (EC) of the National Institute of Geography and Statistics (INEGI). The EC information for 2004 was still not fully compatible with the North America Industry Classification System (NAICS), with 262 of the 309 data at the fourth-digit level aligned to the USA. In addition, industrial information from the EC is recorded every four years, which prevents this study to use panel data techniques and it makes it impossible to use time series methods.

Policymakers can clearly identify competition forces having a significant impact on employment growth. This can orient policymakers to implement measures to encourage the development of some of these clusters, as well as to identify some of the sources that drive specialization, competition and diversity.

This paper contributes to the debate on the existence of Marshallian (MAR), Jacobian and Porter externalities. This is the first study using the definition of traded clusters in Mexico, which allows the authors to identify how specialization, competition and diversity forces drive the dynamics of regional employment growth.