Numerical and Experimental Study on Ventilation Panel Models in a Subway Passenger Compartment

The internal flow field study of car compartments is an important step in railroad vehicle design and optimization. The flow field profile has a significant impact on the temperature distribution and passenger comfort level. Experimental studies on flow field can yield accurate results but carry a high time and computational cost. In contrast, the numerical simulation method can yield an internal flow field profile in less time than an experimental study. This study aims to improve the computational efficiency of numerical simulation by adapting two simplified models—the porous media model and the porous jump face model—to study the internal flow field of a railroad car compartment. The results provided by both simplified models are compared with the original numerical simulation model and with experimental data. Based on the results, the porous media model has a better agreement with the original model and with the experimental results. The flow field parameters (temperature and velocity) of the porous media model have relatively small numerical errors, with a maximum numerical error of 4.7%. The difference between the numerical results of the original model and those of the porous media model is less than 1%. By replacing the original numerical simulation model with the porous media model, the flow field of subway car compartments can be calculated with a reduction of about 25% in computing resources, while maintaining good accuracy.

Health diagnosis of ultrahigh arch dam performance using heterogeneous spatial panel vector model

Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams.A comprehensive analysis was conducted,focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in China.Subsequently,the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored,including periodicity,convergence,and time-effect characteristics.These findings revealed the governing mechanism of main factors.Furthermore,a heterogeneous spatial panel vector model was developed,considering both common factors and specific factors affecting the safety and performance of arch dams.This model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions,introducing a specific effect quantity to characterize local deformation differences.Ultimately,the proposed model was applied to the Xiaowan arch dam,accurately quantifying the spatiotemporal heterogeneity of dam performance.Additionally,the spatiotemporal distri-bution characteristics of environmental load effects on different parts of the dam were reasonably interpreted.Validation of the model prediction enhances its credibility,leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan dam.The findings not only enhance the predictive ability and timely control of ultrahigh arch dams'performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.

A Study on the Relationship Between Land Finance and Housing Price in Urbanization Process: An Empirical Analysis of 182 Cities in China Based on Threshold Panel Models

Scholars have a variety of theoretical explanations for housing price growth. However, few scholars have studied the internal influence mechanism among urbanization, land finance, and housing price. Based on the data of 182 prefecture-level cities from 2009 to 2016, this paper studies the influence of land finance on housing price under different urbanization rate levels. The study finds that with the increase of urbanization rate, the effect of land finance on housing price presents a "U" shape.Specifically, an increase in land finance by 1% results in a corresponding increase in average housing price by 0.18%, with relatively low urbanization rate, 0.06% with medium level of urbanization rate,and 0.38% with high level of urbanization rate.

How R&D investment promotes green technology innovation in the context of digitalization?-An empirical analysis based on provincial panel data

Green technology innovation is an important driving force and source to promote my country’s high-quality development,and it is the core path to achieve sustainable development.This paper uses my country’s provincial panel data from 2016 to 2019 to study the impact mechanism of R&D investment on green technology innovation,and introduces the level of digitization,using the panel threshold model to discuss its role in the impact mechanism of R&D investment on green technology innovation.The study found that when the level of digitalization in a region is low,increasing R&D investment does not necessarily improve the ability of green technology innovation;when the level of digitalization is relatively high,R&D investment has a positive role in promoting green technology innovation.Therefore,it is necessary to improve policies to encourage enterprises to increase investment in research and development;at the same time,it is necessary to promote the coordinated development of digital foundation,digital investment,digital literacy,digital economy and digital application,and promote the deep integration of digitalization and green technology innovation.

Panel data models with cross-sectional dependence: a selective review

In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues of cross-sectional dependence, and introduces the concepts of weak and strong cross-sectional dependence. Then, the main attention is primarily paid to spatial and factor approaches for modeling cross-sectional dependence for both linear and nonlinear （nonparametric and semiparametric） panel data models. Finally, we conclude with some speculations on future research directions.

A review of mid-frequency vibro-acoustic modelling for highspeed train extruded aluminium panels as well as the most recent developments in hybrid modelling techniques

The present paper reviews the vibro-acoustic modelling of extruded aluminium train floor structures including the state-of-the-art of its industrial applications, as well as the most recent developments on mid-frequency mod- elling techniques in general. With the common purpose to predict mid-frequency vibro-acoustic responses of stiffened panel structures to an acceptable accuracy at a reasonable computational cost, relevant techniques are mainly based on one of the following three types of mid-frequency vibro- acoustic modelling principles： （1） enhanced deterministic methods, （2） enhanced statistical methods, and （3） hybrid deterministic/statistical methods. It is shown that, although recent developments have led to a significant step forward in industrial applicability, mature and adequate prediction tech- niques, however, are still very much required for solving sound transmission through, and radiation from, extruded aluminium panels used on high-speed trains. Due to their great potentials for predicting mid-frequency vibro-acoustics of stiffened panel structures, two of recently developed mid-frequency modelling approaches, i.e. the so-called hybrid finite element-statistical energy analysis （FE-SEA） and hybrid wave-based method- statistical energy analysis （WBM-SEA）, are then recapitulated.

Small Sample Estimation in Dynamic Panel Data Models: A Simulation Study

We used simulated data to investigate both the small and large sample properties of the within-groups (WG) estimator and the first difference generalized method of moments (FD-GMM) estimator of a dynamic panel data (DPD) model. The magnitude of WG and FD-GMM estimates are almost the same for square panels. WG estimator performs best for long panels such as those with time dimension as large as 50. The advantage of FD-GMM estimator however, is observed on panels that are long and wide, say with time dimension at least 25 and cross-section dimension size of at least 30. For small-sized panels, the two methods failed since their optimality was established in the context of asymptotic theory. We developed parametric bootstrap versions of WG and FD-GMM estimators. Simulation study indicates the advantages of the bootstrap methods under small sample cases on the assumption that variances of the individual effects and the disturbances are of similar magnitude. The boostrapped WG and FD-GMM estimators are optimal for small samples.

FEM equivalent model for press bend forming of aircraft integral panel

An original plastic equivalent model was proposed to solve the problem of excessive FEM simulation time when designing the press bend forming path and optimizing the process parameters of press bend forming of the integrally stiffened aircraft panels. Based on the in-depth analysis of the mechanics of the bending and springback of the detailed model and the equivalent model of the integral panels,the plastic equivalent model of the virtual material with special initial yield stress and hardening coefficients was constructed. FEM results indicate that the objective of getting the similar contour with the same press bend forming path is achieved with the error less than 6%,and the efficiency of FEM simulation is improved by more than 80%. The plastic equivalent model is valuable and essential for the further research on the press bend forming process of large scale complicated integral panels.

Macro Debt Burden and Consumption Expansion:An Analysis Based on Panel Model and Panel Quantile Regression Model

As the level of social credit burden rises,to ease the liquidity constraint for residents is currently an important way to boost the domestic demand in China.This paper uses the panel data of Chinese provincial-level administrative units in 2007−2017 and adopts the panel regression model and panel quantile regression model to empirically analyze the relationship between debt burden level and average propensity to consume(APC).The result shows that increase in the level of macro debt burden can significantly improve the APC of residents;the marginal promoting effect of macro debt burden for the APC is in a V-shaped structure;such marginal influence differs evidently in different areas,with the marginal promoting effect turning out most prominent in the northeast of China.Accordingly,it’s suggested for government to keep refining the credit market,increase residents’income in multiple means,guide supply of liquidity towards the real economy and promote equalization of basic public services,so as to realize the expansion and upgrade of consumption.

Benefit Analysis of Chemical Fertilizer Input for Staple Grain Production Based on Threshold Panel Data Model

Based on the threshold panel data model,this paper analyzed the nonlinear relationship between chemical fertilizer input and grain output. At the provincial level,from the perspective of average and marginal net benefits,it compared the effects of chemical fertilizer input on farmers' income. It reached the conclusion that the chemical fertilizer input efficiency has deviated from the optimal level. Thus,only by increasing the marginal productivity of chemical fertilizers,may it be able to increase farmers' income.

Comparison of Uniform and Kernel Gaussian Weight Matrix in Generalized Spatial Panel Data Model

Panel data combine cross-section data and time series data. If the cross-section is locations, there is a need to check the correlation among locations. ρ and λ are parameters in generalized spatial model to cover effect of correlation between locations. Value of ρ or λ will influence the goodness of fit model, so it is important to make parameter estimation. The effect of another location is covered by making contiguity matrix until it gets spatial weighted matrix (W). There are some types of W—uniform W, binary W, kernel Gaussian W and some W from real case of economics condition or transportation condition from locations. This study is aimed to compare uniform W and kernel Gaussian W in spatial panel data model using RMSE value. The result of analysis showed that uniform weight had RMSE value less than kernel Gaussian model. Uniform W had stabil value for all the combinations.

Dynamic modeling of spacecraft solar panels deployment with Lie group variational integrator

The spacecraft with multistage solar panels have nonlinear coupling between attitudes of central body and solar panels, especially the rotation of central body is considered in space. The dynamics model is based for dynamics analysis and control, and the multistage solar panels means the dynamics modeling will be very complex. In this research, the Lie group variational integrator method is introduced, and the dynamics model of spacecraft with solar panels that connects together by flexible joints is built. The most obvious character of this method is that the attitudes of central body and solar panels are all described by three-dimensional attitude matrix. The dynamics models of spacecraft with one and three solar panels are established and simulated. The study shows Lie group variational integrator method avoids parameters coupling and effectively reduces difficulty of modeling. The obtained continuous dynamics model based on Lie group is a set of ordinary differential equations and equivalent with traditional dynamics model that offers a basis for the geometry control.

Empirical Research on the Relationship between Education Poverty Alleviation and Rural Revitalization—Spatial Panel Simultaneous Equation Model Based on Provincial Panel Data

On the basis of using entropy weight method to measure China’s education poverty alleviation and rural revitalization evaluation indicators, using the panel data of 30 provinces in China (excluding Xizang, Hong Kong, Macao and Taiwan) from 2012 to 2021, a spatial panel simultaneous equation model is constructed based on adjacency matrix, geographical distance matrix and economic geographical distance matrix deeply study the interaction mechanism and spatial spillover effects between education poverty alleviation and rural revitalization through the generalized spatial three-stage least squares method (GS3SLS). The results indicate that there is a significant spatial spillover effect and a positive spatial correlation between education poverty alleviation and rural revitalization, and there is a significant interactive effect between the two variables, while promoting each other positively. Therefore, the government should clarify the deep relationship between education poverty alleviation and rural revitalization based on the current background, and better consolidate and expand the effective connection between the achievements of education poverty alleviation and rural revitalization.

Comparison of Different Models for the Simulation of Photovoltaic Panels

This article contains the description of a circuital model, which was developed to represent the energy production of a photovoltaic panel in a more accurate way, taking into consideration the decrease of its operational time. Furthermore, a comparison among the experimental, the posed simulated model in PSIM and the results obtained by a piece of software developed by some students of the Universidad Distrital is performed in order to verify the values provided by the software and demonstrate the optimal operation of the developed model.

Some Additional Moment Conditions for a Dynamic Count Panel Data Model with Predetermined Explanatory Variables

This paper proposes some additional moment conditions for the linear feedback model with explanatory variables being predetermined, which is proposed by [1] for the purpose of dealing with count panel data. The newly proposed moment conditions include those associated with the equidispersion, the Negbin I-type model and the stationarity. The GMM estimators are constructed incorporating the additional moment conditions. Some Monte Carlo experiments indicate that the GMM estimators incorporating the additional moment conditions perform well, compared to that using only the conventional moment conditions proposed by [2,3].

The Disagreement between Anisotropic-Isotropic Diffuse Solar Radiation Models as a Function of Solar Declination: Computing the Optimum Tilt Angle of Solar Panels in the Area of Southern-Italy

In this paper a simulation to maximize the global solar radiation on a sloped collecting surface was applied to typical latitudes in the area of southern Italy, to calculate the optimum tilt angle of solar panels on building structures or large photovoltaic power plants located in that geographical area. Indeed, the area of southern Italy and in particular Sicily and Calabria are the top of European locations for acquiring solar energy. Some models of diffuse solar irradiance were taken into account to determine panels inclinations that maximized the impinging solar radiation by means of global horizontal solar radiation data provided from the Italian Institute of ENEA (Italy). An algorithm was used for the simulation providing a set of tilt angles for each latitude. The optimum tilt angle values obtained from the simulation resulted to be strictly related to the model of diffuse solar radiation that was used. Indeed, the disagreement between the values obtained using anisotropic models of diffuse solar radiation and those obtained from the isotropic model resulted to decrease significantly with increasing solar declination, showing that the isotropic model can be reliable only in summer months.

Systematic studies on scan and driving model for flat panel display

Aiming at the time redundancy in the fiat panel display （FPD） imaging process, the paper studied some problems for FPD gray scale controlling based on the fraetal theory, dissertates the construction of the space-time mapping topology architecture, the proposition of optimal scanning structure for FPD＇s gray imaging, and the creation of the fractal theoretic model. Then the logic implementation and system application are presented based on the fraetal model of the optimal scan architecture, and the application results achieved target of eliminating time redundancy and increasing the scanning availability. The novel control mode that the fractal scanning IP core described with Verilog language embedded in the FPGA hardware frame can efficiently increase the imaging gray scales and quality in the FPDs scanning controller and speed up the frame frequency of display system.

34个城市的住宅财富效应:基于panel data的实证研究

本文检验了我国人均消费支出与住宅财富之间的关系。以2001—2004年34个城市为样本,使用面板误差纠正模型估计住宅财富的边际消费倾向,结果表明边际消费倾向为-0.033,并从消费者信贷约束和预防性储蓄角度进行了简要解释。

教育支出的产出效应研究——基于空间Panel Data与菲德模型的数量分析

考虑到我国省际经济增长的空间溢出性和空间相关性,将空间Panel Data模型和菲德模型结合起来研究教育支出的产出效应,这种方法能在考虑空间相关性的基础上研究教育支出的部门溢出,从而对教育支出的产出效应得到更准确的估计。研究结果显示省际经济增长之间存在显著的空间相关性,而空间Panel Data模型的实证结果也表明,如果不考虑空间相关性会夸大教育支出的部门溢出。

基于Panel-data的区际产业转移粘性分析

利用面板数据模型,以江苏省为例,对28个制造业的科技进步、产业集群、区域人力资本积累、沉没成本和资产专用性、劳动力跨区域流动、制度创新、政府阻力等因素对产业转移粘性的关系进行了实证研究,并依据各个因素的贡献率得出了跨区域产业转移的初步结论。