Search results

This paper aims to propose a three-phase interpenetrating continua model for the numerical simulation of water waves and porous structure interaction.

In contrast with one-fluid formulation or multi-component methods, each phase has its own characteristics, density, velocity, etc., and each point is occupied by all phases. First, the porous structure is modelled as a phase of continua with a penalty force adding on the momentum equation, so the conservation of mass is guaranteed without source terms. Second, the adaptive unstructured mesh modelling with P1DG-P1 elements is used here to decrease the total number of degree of freedom maintaining the same order of accuracy.

Several benchmark problems are used to validate the model, which includes the Darcy flow, classical collapse of water column and water column with a porous structure. The interpenetrating continua model is a suitable approach for water wave and porous structure interaction problem.

The interpenetrating continua model is first applied for the water wave and porous structure interaction problem. First, the structure is modelled as phase of non-viscous fluid with penalty force, so the break of the porous structure, porosity changes can be easily embedded for further complex studies. Second, the mass conservation of fluids is automatically satisfied without special treatment. Finally, adaptive anisotropic mesh in space is employed to reduce the computational cost.

The cumulative sum (Cusum) operator, also referred to as accumulating generation operator, is the fundamental of grey system models and proves to be successful in various real-world applications. This paper aims to uncover the advantages of the Cusum operator from a parameter estimation perspective, i.e. comparing integral matching with classical gradient matching.

Grey system models are represented as a state space form to investigate the effect of measurement errors on estimation performance; subsequently, gradient matching and integral matching are respectively formulated to estimate parameters from noisy observations and, then, their quantitative relationships are established by using matrix computation tricks.

Extensive simulations, which are conducted on both linear and non-linear models under different sample size and noise level combinations, show that integral matching is superior to gradient matching, and, also the former is less sensitive to measurement error.

This paper explains why the Cusum operator is widely utilized in grey system models, thereby further solidifying the mathematical fundamentals of grey system models.

In this paper, the authors aim to propose an effective method to indirectly determine nonlinear elastic shear stress-strain constitutive relationships for nonlinear elasticity materials, and then study the nonlinear free torsional vibration of Al–1%Si shaft.

In this study the authors use BoxLucas1 model to fit the determined-experimentally nonlinear elastic normal stress–strain constitutive relationship curve of Al–1%Si, a typical case of isotropic nonlinear elasticity materials, and then derive its nonlinear shear stress-strain constitutive relationships based on the fitting constitutive relationships and general equations of plane-stress and plane-strain transformation. Hamilton’s principle is utilized to gain nonlinear governing equation and boundary conditions for free torsional vibration of Al–1%Si shaft. Differential quadrature method and an iterative algorithm are employed to numerically solve the gained equations of motion.

The effect of four variables, namely dimensionless fundamental vibration amplitude ϑmax, radius α and length β, and nonlinear-elasticity intensity factor δ, on frequencies and mode shapes of the shafts is obtained. Numerical results are in good agreement with reference solutions, and show that compared with linearly elastic shear stress-strain constitutive relationships of the shafts made of the nonlinear elasticity materials, its actual nonlinearly elastic shear stress-strain constitutive relationships have smaller torsion frequencies. In addition, but β having opposite hardening effect, the rest of the four variables have softening effect on nonlinearly elastic torsion frequencies. Eventually, taking into account nonlinearly elastic shear stress-strain constitutive relationships, changes of the four factors, i.e. ϑmax, α, β and δ, cause inflation and deflation behaviors of mode shapes in nonlinear free torsional vibration.

The study could provide a reference for indirectly determining nonlinear elastic shear stress-strain constitutive relationships for nonlinear elasticity materials and for structure design of torsional shaft made of nonlinear elasticity materials.

This chapter develops a set of two-step identification methods for social interactions models with unknown networks, and discusses how the proposed methods are connected to the identification methods for models with known networks. The first step uses linear regression to identify the reduced forms. The second step decomposes the reduced forms to identify the primitive parameters. The proposed methods use panel data to identify networks. Two cases are considered: the sample exogenous vectors span Rn (long panels), and the sample exogenous vectors span a proper subspace of Rⁿ (short panels). For the short panel case, in order to solve the sample covariance matrices’ non-invertibility problem, this chapter proposes to represent the sample vectors with respect to a basis of a lower-dimensional space so that we have fewer regression coefficients in the first step. This allows us to identify some reduced form submatrices, which provide equations for identifying the primitive parameters.

With the rapid-growing house market in the past decade, the purpose of this paper is to study the important issue of house price information flows among 12 major cities in China, including Shanghai, Beijing, Xiamen, Shenzhen, Guangzhou, Hangzhou, Ningbo, Nanjing, Zhuhai, Fuzhou, Suzhou and Dongguan, during the period of June 2010 to May 2019.

The authors approach this issue in both time and frequency domains, latter of which is facilitated through wavelet analysis and by exploring both linear and nonlinear causality under the vector autoregressive framework.

The main findings are threefold. First, in the long run of the time domain and for timescales beyond 16 months of the frequency domain, house prices of all cities significantly affect each other. For timescales up to 16 months, linear causality is weaker and is most often identified for the scale of four to eight months. Second, while nonlinear causality is seldom determined in the time domain and is never found for timescales up to four months, it is identified for scales beyond four months and particularly for those beyond 32 months. Third, nonlinear causality found in the frequency domain is partly explained by the volatility spillover effect.

Results here should be of use to policymakers in certain policy analysis.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

The promotion of new energy vehicles (EVs) is an effective way to achieve low carbon emission reduction. This paper aims to investigate the optimal pricing of automotive supply chain members in the context of dual policy implementation while considering consumers' low-carbon preferences.

This article takes manufacturers, retailers and consumers in a main three-level supply chain as the research object. Stackelberg game theory is used as the theoretical guidance. A game model in which the manufacturer is the leader and the retailer is the follower is established. The author also considered the impact of carbon tax policies, subsidy policies and consumer preferences on the results. Furthermore, the author investigates the optimal decision-making problem under the profit maximization model.

Through model solving, it is found that the pricing of EVs is positively correlated with the unit price of carbon and the amount of subsidies. The following conclusions can be obtained by numerical analysis of each parameter. Changes in carbon prices have a greater impact on conventional gasoline vehicles. Based on the numerical analysis of parameter β, it is also found that when the government subsidizes consumers, supply chain members will increase their prices to obtain partial subsidies. Compared with retailers, low-carbon preferences have a greater impact on manufacturers.

The new energy automobile industry involves many policies, including tax cuts, tax exemptions and subsidies. The policy environment faced by the members of a supply chain is complex and diverse. Therefore, the analysis in this article is based only on partial policies.

The authors innovatively combine the three factors of subsidy policy, carbon tax policy and consumer low-carbon preference, with research on the pricing of EVs. The influence of policy factors and consumer preferences on the pricing of EVs is studied.

This study examines the effect of employees' perceptions of political connections on performance measurement systems (PMS) design choice and firm performance. In addition, this study explores the moderating effect of social networking, a very common and widely used factor by domestic and foreign multinational firms operating in China, and its joint effect with political connections or PMS design choice on firm performance. We collected survey responses from a sample of 110 managers from manufacturing firms in China. Our results reveal that highly politically connected managers use nonfinancial measures, leading to improved firm performance. Our results suggest that social networking interacts significantly with political connections, and nonfinancial and financial measures on firm performance. The theoretical and practical implications of our findings are discussed.

Distance is the core concept in tourism. However, previous studies focused on single distance dimensions and generated contradictory findings due to omitted variable biases. This paper aims to introduce the well-established CAGE (cultural, administrative, geographical, and economic) distance framework into international tourism research to measure the comprehensive distance and explore its impact on inbound tourist satisfaction.

The comprehensive distance was calculated based on the Mahalanobis formula. Combining tourist review data from TripAdvisor, this study used ordinary least square regressions to explore the influence of the comprehensive distance on inbound tourist satisfaction and the mediating role of inbound tourist emotion.

Results show that CAGE distance effectively describes the dynamic change in distance. The comprehensive distance also positively impacts tourist satisfaction, and tourist emotion plays a mediating role in this impact.

This paper advances knowledge about distance in international tourism by introducing the CAGE distance framework and addresses the contradictory findings with specific distance dimensions by the comprehensive distance.

距离是旅游的核心概念。然而, 以前的研究集中在单一的距离维度上, 并且由于遗漏变量偏差而产生了相互矛盾的结果。 本文旨在将成熟的 CAGE 距离框架引入国际旅游研究中, 以衡量综合距离并探讨其对入境游客满意度的影响。

综合距离根据马氏距离公式计算。 结合TripAdvisor网站的游客评论数据, 采用普通最小二乘（OLS）回归分析综合距离对入境游客满意度的影响以及入境游客情绪的中介作用。

结果表明, CAGE距离有效地描述了距离的动态变化。 综合距离也正向影响游客满意度, 游客情绪在此影响中起中介作用。

本文通过引入 CAGE 距离框架来提升国际旅游中的距离知识。 本研究还通过综合距离解决了特定距离维度的矛盾发现。

La distancia es el concepto central en el turismo. Sin embargo, estudios previos se han centrado en dimensiones de una sola distancia, generando resultados contradictorios debido a los sesgos por la omisión de variables. Este trabajo tiene como objetivo introducir el marco de distancia CAGE, establecido en la investigación turística internacional, con la intención de medir la distancia integral y explorar su impacto en la satisfacción del turista receptor.

La distancia integral se calculó con base en la fórmula de Mahalanobis. Combinando los datos de reseñas turísticas de TripAdvisor, se utilizaron regresiones de mínimos cuadrados ordinarios (OLS) para explorar la influencia de la distancia integral en la satisfacción del turista receptor y el papel mediador de la emoción del turista receptor.

Los resultados muestran que el modelo CAGE describe el cambio dinámico en la distancia de una forma efectiva. La distancia integral también impacta positivamente en la satisfacción del turista, y la emoción del turista juega un papel mediador en este impacto.

Este documento avanza en el conocimiento sobre la distancia en el turismo internacional mediante la introducción del marco de distancia CAGE. Además, aborda resultados contradictorios con las dimensiones de distancia específicas mediante la distancia integral.