Stable Runge-Kutta discontinuous Galerkin solver for hypersonic rarefied gaseous flow based on 2D Boltzmann kinetic model equations

A stable high-order Runge-Kutta discontinuous Galerkin(RKDG) scheme that strictly preserves positivity of the solution is designed to solve the Boltzmann kinetic equation with model collision integrals. Stability is kept by accuracy of velocity discretization, conservative calculation of the discrete collision relaxation term, and a limiter. By keeping the time step smaller than the local mean collision time and forcing positivity values of velocity distribution functions on certain points, the limiter can preserve positivity of solutions to the cell average velocity distribution functions. Verification is performed with a normal shock wave at a Mach number 2.05, a hypersonic flow about a two-dimensional(2D) cylinder at Mach numbers 6.0 and 12.0, and an unsteady shock tube flow. The results show that, the scheme is stable and accurate to capture shock structures in steady and unsteady hypersonic rarefied gaseous flows. Compared with two widely used limiters, the current limiter has the advantage of easy implementation and ability of minimizing the influence of accuracy of the original RKDG method.

Numerical simulation of metal evaporation based on the kinetic model equation and the direct simulation Monte Carlo method

Metal evaporation on the basis of the kinetic model equations(BGK and S-model) and the direct simulation Monte Carlo(DSMC) method was investigated computationally under the circumstances of collimators existing or not. Numerical data of distributions of number density, bulk velocity and temperature were reported over a wide range of evaporation rate.It was shown that these results reached a good agreement for the case of small evaporation rate, while the deviations became increasingly obvious with the increase of evaporation rate, especially when the collimators existed. Moreover, the deposition thickness over substrate obtained from the kinetic model equations were inaccurate even though the evaporation rate was small. All of the comparisons showed the reliability of the kinetic model equations, which require less computational cost at small evaporation rate and simple structure.

DIRECT NUMERICAL TEST OF THE B-G-K MODEL EQUATION BY THE DSMC METHOD

In the present paper the rarefied gas how caused by the sudden change of the wall temperature and the Rayleigh problem are simulated by the DSMC method which has been validated by experiments both in global flour field and velocity distribution function level. The comparison of the simulated results with the accurate numerical solutions of the B-G-K model equation shows that near equilibrium the BG-K equation with corrected collision frequency can give accurate result but as farther away from equilibrium the B-G-K equation is not accurate. This is for the first time that the error caused by the B-G-K model equation has been revealed.

A practical guideline for univariate meta-analytic structural equation modelling

Background:Meta-analysis is a quantitative approach that systematically integrates results from previous research to draw conclusions.Structural equation modelling is a statistical method that integrates factor analysis and path analysis.Meta-analytic structural equation modeling(MASEM)combines meta-analysis and structural equation modeling.It allows researchers to explain relationships among a group of variables across multiple studies.Methods:We used a simulated dataset to conduct a univariate MASEM analysis,using Comprehensive Meta Analysis 3.3,Analysis of Moment Structures 24.0 software.Results:Despite the lack of concise literature on the methodology,our study provided a practical step-by-step guide on univariate MASEM.Conclusion:Researchers can employ MASEM analysis in applicable fields based on the description,principles,and practices expressed in this study and our previous publications mentioned in this study.

Measurement Research Based on Bayesian Structural Equation Cognitive Model

The Bayesian structural equation model integrates the principles of Bayesian statistics, providing a more flexible and comprehensive modeling framework. In exploring complex relationships between variables, handling uncertainty, and dealing with missing data, the Bayesian structural equation model demonstrates unique advantages. Therefore, Bayesian methods are used in this paper to establish a structural equation model of innovative talent cognition, with the measurement of college students’ cognition of innovative talent being studied. An in-depth analysis is conducted on the effects of innovative self-efficacy, social resources, innovative personality traits, and school education, aiming to explore the factors influencing college students’ innovative talent. The results indicate that innovative self-efficacy plays a key role in perception, social resources are significantly positively correlated with the perception of innovative talents, innovative personality tendencies and school education are positively correlated with the perception of innovative talents, but the impact is not significant.

A Survey Study on TPACK Framework for Normal Students of English Major in Ethnic Colleges and Universities:Empirical Analysis Based on Structural Equation Modeling

With the continuous advancement of education informatization,Technological Pedagogical Content Knowledge(TPACK),as a new theoretical framework,provides a novel method for measuring teachers’informatization teaching ability.This study takes normal students of English majors from three ethnic universities as the research object,collects relevant data through questionnaires,and uses structural equation modeling to conduct data analysis and empirical research to investigate the differences in the TPACK levels of these students at different grades and the structural relationships among the elements in the TPACK structure.The technological pedagogical knowledge element of the TPACK structure was not obtained by exploratory factors analysis but through path analysis and structural equation modeling,the results show that the one-dimensional core knowledge of technological knowledge(TK),content knowledge(CK),and pedagogical knowledge(PK)have a positive effect on the two-dimensional interaction knowledge of technological content knowledge(TCK)and pedagogical content knowledge(PCK);furthermore,TCK and PCK have a positive effect on TPACK;and TK,CK,and PK indirectly affect TPACK through TCK and PCK.On this basis,suggestions are provided to ethnic colleges and universities to develop the TPACK knowledge competence of normal students of English majors.

Numerical study on the gas-kinetic high-order schemes for solving Boltzmann model equation

The high-order compact finite difference technique is introduced to solve the Boltzmann model equation, and the gas-kinetic high-order schemes are developed to simulate the different kinetic model equations such as the BGK model, the Shakhov model and the Ellipsoidal Statistical (ES) model in this paper. The methods are tested for the one-dimensional unsteady shock-tube problems with various Knudsen numbers, the inner flows of normal shock wave for different Mach numbers, and the two-dimensional flows past a circular cylinder and a NACA 002 airfoil to verify the reliability of the present high-order algorithm and simulate gas transport phenomena covering various flow regimes. The computed results are found in good agreement both with the theoretical prediction from continuum to rarefied gas dynamics, the related DSMC solutions, and with the experimental results. The numerical effect of the schemes with the different precision and the different types of Boltzmann collision models on the computational efficiency and computed results is investigated and analyzed. The numerical experience indicates that an approach developing and applying the gas-kinetic high-order algorithm is feasible for directly solving the Boltzmann model equation.

Coupling Relationship Analysis on Households′ Production Behaviors and Their Influencing Factors in Nature Reserves:A Structural Equation Model

A households′production behavior directly influences the quality of the environment and determines the successful development of nature reserves.Meanwhile,the households′production behaviors are complicated by interrelated factors,such as protection attitudes,resource endowment,and family wealth.This research evaluated households near the Crested Ibis National Nature Reserve in Shaanxi Province,acquiring data from 436 households around Yang County and Ningshan County in the south slope of Qinling Mountains,China.Based on the collected data,we developed a structural equation model to evaluate the coupling relationships among households′ protection attitudes,production behaviors,resource endowment,and family wealth.The results showed that:1) households with great resource endowment had more negative attitudes,probably due to their greater protection costs;2) the households with higher education levels had worse protection attitudes;3) the households with more family wealth were likely to use fewer fertilizers,pesticides,and firewood;4) the households with more resource endowment showed less production and management behaviors;5) the enhancement of households' attitudes improved production behaviors to protection the environment,but the effects were not statistically significant.Our results provide a basis for the government's protection policy making,exploring the effective management measures that are beneficial for both nature reserve management and community development.

Investigation of the role of personal factors on work injury in underground mines using structural equation modeling

Work injuries in mines are complex and generally characterized by several factors starting from personal to technical and technical to social characteristics.In this paper,investigation was made through the application of structural equation modeling to study the nature of relationships between the influencing/associating personal factors and work injury and their sequential relationships leading towards work injury occurrences in underground coal mines.Six variables namely,rebelliousness,negative affectivity,job boredom,job dissatisfaction and work injury were considered in this study.Instruments were developed to quantify them through a questionnaire survey.Underground mine workers were randomly selected for the survey.Responses from 300 participants were used for the analysis.The structural model of LISREL was used to estimate the interrelationships amongst the variables.The case study results show that negative affectivity and job boredom induce more job dissatisfaction to the workers whereas risk taking attitude of the individual is positively influenced by job dissatisfaction as well as by rebelliousness characteristics of the individual.Finally,risk taking and job dissatisfaction are having positive significant direct relationship with work injury.The findings of this study clearly reveal that rebelliousness,negative affectivity and job boredom are the three key personal factors influencing work related injuries in mines that need to be addressed properly through effective safety programs.

Factors influencing the internet banking adoption decision in North Cyprus: an evidence from the partial least square approach of the structural equation modeling

Purpose:This paper aims to examine how the adoption decision of the internet banking in North Cyprus would be affected based on the following dimensions;the technology features,the personal characteristics,the social environment and the expected risk.Design/methodology/approach:A self-administered survey was conducted with 291 participants responded to it.The partial least square approach of the structural equation modeling(PLS-SEM)is employed to investigate the direct effects of the proposed factors on the adoption decision.Additionally,the mediation test is used to examine indirect effects.Findings:Results showed that even though the participants appreciated the benefits of the online banking as the perceived usefulness factor exerts the greatest direct effect,they would rather use clear and easy-to-use websites,adding to that their assessments of the usefulness of these services are significantly influenced by the surrounding people’s views and prior experience.This is demonstrated by the total effects of the perceived ease of use and the subjective norm factors,which are greater than the direct effect of the perceived usefulness factor since both of these factors have significant direct and indirect effects mediated by the perceived usefulness factor.The negative impact of the perceived risk factor is weak compared to the previous factors.While the personal innovativeness factor showed the weakest effect among the proposed factors.

Frequency domain wave equation forward modeling using gaussian elimination with static pivoting

Frequency domain wave equation forward modeling is a problem of solving large scale linear sparse systems which is often subject to the limits of computational efficiency and memory storage. Conventional Gaussian elimination cannot resolve the parallel computation of huge data. Therefore, we use the Gaussian elimination with static pivoting （GESP） method for sparse matrix decomposition and multi-source finite-difference modeling. The GESP method does not only improve the computational efficiency but also benefit the distributed parallel computation of matrix decomposition within a single frequency point. We test the proposed method using the classic Marmousi model. Both the single-frequency wave field and time domain seismic section show that the proposed method improves the simulation accuracy and computational efficiency and saves and makes full use of memory. This method can lay the basis for waveform inversion.

Quality Management Model for Phase I Clinical Drug Trials:A Structural Equation Model

This study aimed to construct a quality management model for phase I clinical drug trials.A cross-sectional survey was conducted and data were collected from 604 respondents at 69 institutions in China engaged in phase I clinical drug trials.Exploratory and confirmatory factor analyses were used to develop the survey tool.Structural equation modeling was used to construct a quality management model for phase I clinical drug trials.The results showed that the final survey tool had good reliability and validity(Cronbach’sα=0.938,root mean square error of approximation=0.074,comparative fit index=0.962,and Tucker—Lewis index=0.955).The model included five dimensions:government regulation,industry management,medical institution management,research team management,and contract research organization(CRO)management.In total,22 measurement items were obtained.The structural equation model indicated government regulation,industry management,medical institution management,and CRO management significantly affected the quality of phase I clinical drug trials(β=0.195,β=0.331,β=0.279,andβ=−0.267,respectively;P<0.05).Research team management had no effect on the quality of trials(β=0.041,P=0.610).In conclusion,the model is valuable for identifying factors influencing phase I clinical drug trials and guiding quality management practices.

Structural equation modeling analysis of factors influencing architects' trust in project design teams

This paper describes a structural equation modeling （SEM） analysis of factors influencing architects＇ trust in project design teams. We undertook a survey of architects, during which we distributed 193 questionnaires in 29 A-level architectural design institutes selected radomly from the altogether 59 ones in Shenzhen, P. R. China, and received 130 valid questionnaires. We used Amos 6.0 for SEM to identify significant personal construct based factors affecting interpersonal trust. The results show that only social interaction between architects significantly affects their interpersonal trust. The explained variance of trus~ is not very high in the model. Therefore, future research should add more factors into the current model. The practical implication is that team managers should promote the social interactions between team members such that the interpersonal trust level between team members can be improved.

Application of Structural Equation Modeling to Evaluate Service Quality of Sportswear Retailing

Structural Equation Modeling （SEM） used widely in sociology, economics and psychology is adopted. Based on data obtained from marketing research, and using statistical analysis software SPSSll. 0 and LISRELS. 7, Theory of Five Dimensions of service quality is proved to be suitable in sportswear retailing in China. It analyzes the relationship among five dimensions and puts them in order of importance as to service quality in sportswear retailing. Advices are given for sportswear retail companies to improve their .Service quality and enhance customer loyalty.

The Korteweg-de Vires equation for the bidirectional pedestrian flow model considering the next-nearest-neighbor effect

This paper focuses on a two-dimensional bidirectional pedestrian flow model which involves the next-nearest-neighbor effect. The stability condition and the Korteweg-de Vries （KdV） equation are derived to describe the density wave of pedestrian congestion by linear stability and nonlinear analysis. Through theoretical analysis, the soliton solution is obtained.

Prediction of Henry's constant in polymer solutions using PCOR equation of state coupled with an activity coefficient model

In this paper,the polymer chain of rotator(PCOR) equation of state(EOS) was used together with an EOS/G^E mixing rule(MHV1) and the Wilson's equation as an excess-Gibbs-energy model in the proposed approach to extend the capability and improve the accuracy of the PCOR EOS for predicting the Henry's constant of solutions containing polymers.The results of the proposed method compared with two equation of state(van der Waals and GC-Flory) and three activity coefficient models(UNIFAC,UNIFAC-FV and Entropic-FV) indicated that the PCOR EOS/Wilson's equation provided more accurate results.The interaction parameters of Wilson's equation were fitted with Henry's constant experimental data and the property parameters of PCOR,a and b,were fitted with experimental volume data(Tait equation).As a result,the present work provided a simple and useful model for prediction of Henry's constant for polymer solutions.

Linking Structural Equation Modeling with Bayesian Network and Its Application to Coastal Phytoplankton Dynamics in the Bohai Bay

Bayesian networks （BN） have many advantages over other methods in ecological modeling, and have become an increasingly popular modeling tool. However, BN are flawed in regard to building models based on inadequate existing knowledge. To overcome this limitation, we propose a new method that links BN with structural equation modeling （SEM）. In this method, SEM is used to improve the model structure for BN. This method was used to simulate coastal phytoplankton dynamics in the Bohai Bay. We demonstrate that this hybrid approach minimizes the need for expert elicitation, generates more reasonable structures for BN models, and increases the BN model＇s accuracy and reliability. These results suggest that the inclusion of SEM for testing and verifying the theoretical structure during the initial construction stage improves the effectiveness of BN models, especially for complex eco-environment systems. The results also demonstrate that in the Bohai Bay, while phytoplankton biomass has the greatest influence on phytoplankton dynamics, the impact of nutrients on phytoplankton dynamics is larger than the influence of the physical environment in summer. Furthermore, although the Redfield ratio indicates that phosphorus should be the primary nutrient limiting factor, our results show that silicate plays the most important role in regulating phytoplankton dynamics in the Bohai Bay.

A Re-Parametrization-Based Bayesian Differential Analysis Algorithm for Gene Regulatory Networks Modeled with Structural Equation Models

Under different conditions,gene regulatory networks(GRNs)of the same gene set could be similar but different.The differential analysis of GRNs under different conditions is important for understanding condition-specific gene regulatory relationships.In a naive approach,existing GRN inference algorithms can be used to separately estimate two GRNs under different conditions and identify the differences between them.However,in this way,the similarities between the pairwise GRNs are not taken into account.Several joint differential analysis algorithms have been proposed recently,which were proved to outperform the naive approach apparently.In this paper,we model the GRNs under different conditions with structural equation models(SEMs)to integrate gene expression data and genetic perturbations,and re-parameterize the pairwise SEMs to form an integrated model that incorporates the differential structure.Then,a Bayesian inference method is used to make joint differential analysis by solving the integrated model.We evaluated the performance of the proposed re-parametrization-based Bayesian differential analysis(ReBDA)algorithm by running simulations on synthetic data with different settings.The performance of the ReBDA algorithm was demonstrated better than another state-of-the-art joint differential analysis algorithm for SEMs ReDNet obviously.In the end,the ReBDA algorithm was applied to make differential analysis on a real human lung gene data set to illustrate its applicability and practicability.

Modeling Dynamic Systems by Using the Nonlinear Difference Equations Based on Genetic Programming

When acquaintances of a model are little or the model is too complicate to build by using traditional time series methods, it is convenient for us to take advantage of genetic programming (GP) to build the model. Considering the complexity of nonlinear dynamic systems, this paper proposes modeling dynamic systems by using the nonlinear difference e-quation based on GP technique. First it gives the method, criteria and evaluation of modeling. Then it describes the modeling algorithm using GP. Finally two typical examples of time series are used to perform the numerical experiments. The result shows that this algorithm can successfully establish the difference equation model of dynamic systems and its predictive result is also satisfactory.

A Structural Equation Model of Residents' Support for Mega Event

The aim of this article is to develop a structural equation model to assess key factors of residents' support for hosting mega event based on previous literature.The model consisted of five latent constructs and eight path hypotheses.A survey was conducted in Shanghai before 2010 World Expo.It was found that the support for mega events is affected directly and/or indirectly by four determinants factors:perceived benefits,perceived costs,personal benefits and community attachment,and support relies heavily on perceived benefits rather than costs.This study contributes to the existing body of knowledge in an attempt to understand local residents' support for a mega event in different economic and cultural settings.