Journal articles: 'Dynamic structural equation models'

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Asparouhov, Tihomir, Ellen L. Hamaker, and Bengt Muthén. "Dynamic Structural Equation Models." Structural Equation Modeling: A Multidisciplinary Journal 25, no. 3 (December 27, 2017): 359–88. http://dx.doi.org/10.1080/10705511.2017.1406803.

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Grimm, Kevin J., and Nilam Ram. "Latent Growth and Dynamic Structural Equation Models." Annual Review of Clinical Psychology 14, no. 1 (May 7, 2018): 55–89. http://dx.doi.org/10.1146/annurev-clinpsy-050817-084840.

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Fontanella, Lara, Luigi Ippoliti, and Pasquale Valentini. "Environmental pollution analysis by dynamic structural equation models." Environmetrics 18, no. 3 (2007): 265–83. http://dx.doi.org/10.1002/env.835.

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Shina, Arya Fendha Ibnu. "ESTIMASI PARAMETER PADA SISTEM MODEL PERSAMAAN SIMULTAN DATA PANEL DINAMIS DENGAN METODE 2 SLS GMM-AB." MEDIA STATISTIKA 11, no. 2 (December 30, 2018): 79–91. http://dx.doi.org/10.14710/medstat.11.2.79-91.

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Single equation models ignore interdependencies or two-way relationships between response variables. The simultaneous equation model accommodates this two-way relationship form. Two Stage Least Square Generalized Methods of Moment Arellano and Bond (2 SLS GMM-AB) is used to estimate the parameters in the simultaneous system model of dynamic panel data if each structural equation is exactly identified or over identified. In the simultaneous equation system model with dynamic panel data, each structural equation and reduced form is a dynamic panel data regression equation. Estimation of structural equations and reduced form using Ordinary Least Square (OLS) resulted biased and inconsistent estimators. Arellano and Bond GMM method (GMM AB) estimator produces unbiased, consistent, and efficient estimators.The purpose of this paper is to explain the steps of 2 SLS GMM-AB method to estimate parameter in simultaneous equation model with dynamic panel data. Keywords:2 SLS GMM-AB, Arellano and Bond estimator, Dynamic Panel Data, Simultaneous Equations

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Cziráky, Dario. "Estimation of dynamic structural equation models with latent variables." Advances in Methodology and Statistics 1, no. 1 (January 1, 2004): 185–204. http://dx.doi.org/10.51936/toxt5757.

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The paper proposes a time series generalisation of the structural equation model with latent variables (SEM). An instrumental variable estimator is considered and its asymptotic properties are analysed. Special emphases are placed on the potential use of the lagged observed variables as instruments and consistency of such estimation is established under some general assumptions about the stochastic properties of the modelled variables. In addition, an identification procedure suitable both for static and dynamic structural equation models is described. The methods are illustrated in an empirical application to dynamic panel estimation of a consumption function using UK household data.

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McNeish, Daniel. "Two-Level Dynamic Structural Equation Models with Small Samples." Structural Equation Modeling: A Multidisciplinary Journal 26, no. 6 (March 28, 2019): 948–66. http://dx.doi.org/10.1080/10705511.2019.1578657.

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Wang, Yulin, Yu Luo, Hulin Wu, and Hongyu Miao. "Dynamic structural equation models for directed cyclic graphs: the structural identifiability problem." Statistics and Its Interface 12, no. 3 (2019): 365–75. http://dx.doi.org/10.4310/sii.2019.v12.n3.a2.

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Wang, Yulin, Yu Luo, Hulin Wu, and Hongyu Miao. "Dynamic structural equation models for directed cyclic graphs: the structural identifiability problem." Statistics and Its Interface 12, no. 3 (2019): 365–75. http://dx.doi.org/10.4310/18-sii550.

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Afonin, S. M. "Structural Schemes and Structural-Parametric Models of Electroelastic Actuators for Nanomechatronics Systems." Mekhatronika, Avtomatizatsiya, Upravlenie 20, no. 4 (April 10, 2019): 219–29. http://dx.doi.org/10.17587/mau.20.219-229.

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The parametric structural schemes, structural-the parametric models and the transfer functions of the electroelastic actuators for the nanomechatronics systems are obtained. The transfer functions of the piezoactuator are determined under the generalized piezoelectric effect. The changes in the elastic compliance and the stiffness of the piezoactuator are found, taking into account the type of control. The decision wave equation and the structural-parametric models of the electroelastic actuators are obtained. Effects of the geometric and physical parameters of the electroelastic actuators and the external load on its static and dynamic characteristics are determined. The parameteric structural schemes for the electroelastic actuators for the nanomechatronics systems are obtained. The transfer functions are determined. For calculation of the automatic control systems for the nanometric movements with the electroelastic actuators are obtained the parametric structural schemes and the transfer functions of actuators. Static and dynamic characteristics of the electroelastic actuators are determined. The application of electroelastic actuators solves problems of the precise matching in microelectronics and nanotechnology, compensation of temperature and gravitational deformations, atmospheric turbulence by wave front correction. By solving the wave equation with allowance for the corresponding equations of the piezoelectric effect, the boundary conditions on loaded working surfaces of the electroelastic actuator, the strains along the coordinate axes, it is possible to construct the structural parametric model of the actuator. The transfer functions and the parametric structural schemes of the electroelastic actuator are obtained from the equations describing the corresponding structural parametric models and taking into account the opposed electromotive force of the electroelastic actuator for the nanomechatronics systems.

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Sagan, Adam. "Dynamic Structural Equation Models in Momentary Assessment in Consumer Research." Marketing i Zarządzanie 54 (2018): 61–73. http://dx.doi.org/10.18276/miz.2018.54-05.

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Valentini, Pasquale, Luigi Ippoliti, and Lara Fontanella. "Modeling US housing prices by spatial dynamic structural equation models." Annals of Applied Statistics 7, no. 2 (June 2013): 763–98. http://dx.doi.org/10.1214/12-aoas613.

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Prindle, John J., and John J. McArdle. "An Examination of Statistical Power in Multigroup Dynamic Structural Equation Models." Structural Equation Modeling: A Multidisciplinary Journal 19, no. 3 (July 20, 2012): 351–71. http://dx.doi.org/10.1080/10705511.2012.687661.

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Supriyanto, Supriyanto. "Analysis of Social, Economic and Population in Central Java Using the Dynamic Data Panel Simultaneous Equation Model." JSSH (Jurnal Sains Sosial dan Humaniora) 3, no. 1 (August 13, 2019): 79. http://dx.doi.org/10.30595/jssh.v3i1.4309.

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A single equation model that is often used ignores the interdependence between response variables. Frequently encountered variables that have a two-way relationship. These interrelated two-way relationships can be summarized in a simultaneous equation model system. There is a relationship between variables which are in fact dynamic. In the system model of simultaneous equations with dynamic panel data, each structural equation is a dynamic panel data regression equation. The estimation of using Ordinary Least Square (OLS) in the dynamic panel data model results in biased and inconsistent predictors because there is a lag of the dependent variable that correlates with the error. First difference in dynamic panel models is used to eliminate individual effects. Instrument variables are needed, namely variables that do not correlate with errors. Therefore, dynamic panel data models are more suitable to be used in analyzing poverty and social change. From the simultaneous equation model obtained, the dominant factors affecting the level of poverty in Central Java Province are the unemployment rate, Human Development Index, labor force participation rate, population, and Gross Regional Domestic Product.

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Hsiao, Cheng, and Qiankun Zhou. "JIVE FOR PANEL DYNAMIC SIMULTANEOUS EQUATIONS MODELS." Econometric Theory 34, no. 6 (November 2, 2017): 1325–69. http://dx.doi.org/10.1017/s0266466617000421.

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We consider the method of moments estimation of a structural equation in a panel dynamic simultaneous equations model under different sample size combinations of cross-sectional dimension, N, and time series dimension, T. Two types of linear transformation to remove the individual-specific effects from the model, first difference and forward orthogonal demeaning, are considered. We show that the Alvarez and Arellano (2003) type GMM estimator under both transformations is consistent only if ${T \over N} \to 0$ as $\left( {N,T} \right) \to \infty $. However, it is asymptotically biased if ${{{T^3}} \over N} \to \kappa \ne 0 < \infty$ as $\left( {N,T} \right) \to \infty $. Since the validity of statistical inference depends critically on whether an estimator is asymptotically unbiased, we suggest a jackknife bias reduction method and derive its limiting distribution. Monte Carlo studies are conducted to demonstrate the importance of using an asymptotically unbiased estimator to obtain valid statistical inference.

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Penny, W. D., K. E. Stephan, A. Mechelli, and K. J. Friston. "Modelling functional integration: a comparison of structural equation and dynamic causal models." NeuroImage 23 (January 2004): S264—S274. http://dx.doi.org/10.1016/j.neuroimage.2004.07.041.

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Akashi, Kentaro, and Naoto Kunitomo. "The limited information maximum likelihood approach to dynamic panel structural equation models." Annals of the Institute of Statistical Mathematics 67, no. 1 (December 13, 2013): 39–73. http://dx.doi.org/10.1007/s10463-013-0438-5.

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Magrini, Alessandro. "Distributed-lag Linear Structural Equation Models in R: the dlsem Package." Austrian Journal of Statistics 48, no. 2 (January 26, 2019): 14–42. http://dx.doi.org/10.17713/ajs.v48i2.777.

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In this paper, an extension of linear Markovian structural causal models is introduced,called distributed-lag linear structural equation models (DLSEMs),where each factor of the joint probability distribution is adistributed-lag linear regression with constrained lag shapes.DLSEMs account for temporal delays in the dependence relationshipsamong the variables and allow to assess dynamic causal effects.As such, they represent a suitable methodology to investigate the effectof an external impulse on a multidimensional system through time.In this paper, we present the dlsem package for Rimplementing inference functionalities for DLSEMs.The use of the package is illustrated through an example on simulated dataand a real-world application aiming at assessing the impact of agriculturalresearch expenditure on multiple dimensions in Europe.

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Williams, Richard, Paul D. Allison, and Enrique Moral-Benito. "Linear Dynamic Panel-data Estimation Using Maximum Likelihood and Structural Equation Modeling." Stata Journal: Promoting communications on statistics and Stata 18, no. 2 (June 2018): 293–326. http://dx.doi.org/10.1177/1536867x1801800201.

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Panel data make it possible both to control for unobserved confounders and to include lagged, endogenous regressors. However, trying to do both simultaneously leads to serious estimation difficulties. In the econometric literature, these problems have been addressed by using lagged instrumental variables together with the generalized method of moments, while in sociology the same problems have been dealt with using maximum likelihood estimation and structural equation modeling. While both approaches have merit, we show that the maximum likelihood–structural equation models method is substantially more efficient than the generalized method of moments method when the normality assumption is met and that the former also suffers less from finite sample biases. We introduce the command xtdpdml, which has syntax similar to other Stata commands for linear dynamic panel-data estimation. xtdpdml greatly simplifies the structural equation model specification process; makes it possible to test and relax many of the constraints that are typically embodied in dynamic panel models; allows one to include time-invariant variables in the model, unlike most related methods; and takes advantage of Stata's ability to use full-information maximum likelihood for dealing with missing data. The strengths and advantages of xtdpdml are illustrated via examples from both economics and sociology.

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Ding, Ke Wei. "The Thermoelastic Dynamic Response of Thick Closed Laminated Shell." Shock and Vibration 12, no. 4 (2005): 283–91. http://dx.doi.org/10.1155/2005/479794.

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Giving up any assumptions about displacement models and stress distribution, weak formulation of mixed state equations including boundary conditions of laminated cylindrical shell are presented. Thermal stresses mixed Hamilton equation of closed cylindrical shell is established. The analytical solutions are obtained for the thermoelastic dynamic response of a thick closed laminated shell subjected to temperature variation. Every equation of elasticity can be satisfied, and all elastic constants can be taken into account. Arbitrary precision of a desired order can be obtained.

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Song, Yanyan, Boyan Chang, Guoguang Jin, Zhan Wei, and Bo Li. "An Approach for the Impact Dynamic Modeling and Simulation of Planar Constrained Metamorphic Mechanism." Shock and Vibration 2020 (August 5, 2020): 1–18. http://dx.doi.org/10.1155/2020/8837838.

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This paper studied the impact dynamic modeling of the planar constrained metamorphic mechanism (PCMM) during configuration transformation. Based on the dynamic theory of the multi-rigid-body system and the coefficient of restitution equation, a new method for dynamic modeling of PCMM considering impact motions generated by configuration transformation is presented, which can be treated as a theoretical foundation for performance design and dynamic control. Firstly, the topology theory based on the impact motion can be classified as the stable impact motion and the mobile impact motion, which is the prerequisite for dynamic modeling and simulation. Secondly, the stable and mobile impact dynamic models for PCMM are established according to the dynamic theory of the multi-rigid-body system. Then, using these models, the corresponding impulse solving models are deduced combining with the coefficient of restitution equation. Finally, the examples of the stable impact motion and the mobile impact motion are respectively given, and the configuration-complete dynamic simulations are carried out. By comparing with the dynamic models without considering the impact motion, the dynamic characteristics of PCMM are analyzed. The theory and method proposed in this paper can be also applied in general planar robotic systems to deal with the problem of internal collision dynamics.

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El MARAGHY, W. H., H. A. El MARAGHY, and A. IBRAHIM. "BONDGRAPH MODELLING OF ROBOT DYNAMICS." Transactions of the Canadian Society for Mechanical Engineering 13, no. 4 (December 1989): 123–32. http://dx.doi.org/10.1139/tcsme-1989-0019.

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Euler-Lagrange and Newton-Euler dynamic modelling become very involved and the equations quite complex even for a robot of few axes. For robot models, the bondgraph approach provides several advantages such as explicit bondgraph representation of the robot physical parameters and does not involve any complex equation writing or matrix inversion. In this paper, the use of the bondgraph method for modelling and simulating robot dynamics is presented. To illustrate the technique, a dynamic model for a SCARA robot is derived using bondgraph modelling. The causality conflict arising from the dependent inertias is solved by introducing structural and joint damping. Simulation results obtained using the developed model were in very close agreement with the analytical values obtained using the manipulator kinematic relations. Response due to impact excitation was obtained and is presented.

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KIEN, P. H., and P. K. HUNG. "THE STRUCTURAL AND DYNAMIC PROPERTIES OF COBALT METAL UNDER TEMPERATURE." Modern Physics Letters B 27, no. 30 (November 21, 2013): 1350223. http://dx.doi.org/10.1142/s0217984913502230.

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In this paper, cobalt metal is investigated by molecular dynamics (MD) simulation with the Pak–Doyam potential. The models of cobalt metal are constructed in a wide temperature range. The simulation reveals that the cobalt metal may exist in three phases: amorphous, nano-crystalline and liquid in the temperature range from 200 K to 1500 K. The structure of obtained models Co is analyzed through the radial distribution function (RDF), coordination number distribution and dependence of the Wendt–Abraham ratio defined as g min /g max under temperature. The simulation found a large number of native vacancies depending on the relaxation degree. The number of these native vacancies can play a role of diffusion vehicle for cobalt atom in amorphous matrix. The diffusion coefficient of cobalt atom in liquid and amorphous phases is evaluated by Einstein equation and concentration of native vacancies.

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McNeish, Daniel, and Ellen L. Hamaker. "A primer on two-level dynamic structural equation models for intensive longitudinal data in Mplus." Psychological Methods 25, no. 5 (October 2020): 610–35. http://dx.doi.org/10.1037/met0000250.

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Castro, Luciano, and Antonio F. Galvao. "Dynamic Quantile Models of Rational Behavior." Econometrica 87, no. 6 (2019): 1893–939. http://dx.doi.org/10.3982/ecta15146.

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This paper develops a dynamic model of rational behavior under uncertainty, in which the agent maximizes the stream of future τ‐quantile utilities, for τ ∈ (0,1). That is, the agent has a quantile utility preference instead of the standard expected utility. Quantile preferences have useful advantages, including the ability to capture heterogeneity and allowing the separation between risk aversion and elasticity of intertemporal substitution. Although quantiles do not share some of the helpful properties of expectations, such as linearity and the law of iterated expectations, we are able to establish all the standard results in dynamic models. Namely, we show that the quantile preferences are dynamically consistent, the corresponding dynamic problem yields a value function, via a fixed point argument, this value function is concave and differentiable, and the principle of optimality holds. Additionally, we derive the corresponding Euler equation, which is well suited for using well‐known quantile regression methods for estimating and testing the economic model. In this way, the parameters of the model can be interpreted as structural objects. Therefore, the proposed methods provide microeconomic foundations for quantile regression methods. To illustrate the developments, we construct an intertemporal consumption model and estimate the discount factor and elasticity of intertemporal substitution parameters across the quantiles. The results provide evidence of heterogeneity in these parameters.

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Srisuma, Sorawoot. "IDENTIFICATION IN DISCRETE MARKOV DECISION MODELS." Econometric Theory 31, no. 3 (September 23, 2014): 521–38. http://dx.doi.org/10.1017/s0266466614000437.

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We derive conditions for the identification of the structural parameters in Markov decision model under the assumptions of Rust (1987, Econometrica 55, 999–1033) when the payoff function is parametrically specified. Identification in this class of dynamic problems is difficult to establish since the parameters of interest enter the value function nonlinearly, and the value function is only defined implicitly as a fixed point of some functional equation. We show it is sufficient to verify identification in the pseudomodel, which is more tractable as it is originally designed to reduce the computational burden in the estimation problem, for the identification of the data generating parameter of the underling model. Our results extend naturally to a class of dynamic discrete action games commonly used in empirical industrial organizations.

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Zyphur, Michael J., Manuel C. Voelkle, Louis Tay, Paul D. Allison, Kristopher J. Preacher, Zhen Zhang, Ellen L. Hamaker, et al. "From Data to Causes II: Comparing Approaches to Panel Data Analysis." Organizational Research Methods 23, no. 4 (May 24, 2019): 688–716. http://dx.doi.org/10.1177/1094428119847280.

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This article compares a general cross-lagged model (GCLM) to other panel data methods based on their coherence with a causal logic and pragmatic concerns regarding modeled dynamics and hypothesis testing. We examine three “static” models that do not incorporate temporal dynamics: random- and fixed-effects models that estimate contemporaneous relationships; and latent curve models. We then describe “dynamic” models that incorporate temporal dynamics in the form of lagged effects: cross-lagged models estimated in a structural equation model (SEM) or multilevel model (MLM) framework; Arellano-Bond dynamic panel data methods; and autoregressive latent trajectory models. We describe the implications of overlooking temporal dynamics in static models and show how even popular cross-lagged models fail to control for stable factors over time. We also show that Arellano-Bond and autoregressive latent trajectory models have various shortcomings. By contrasting these approaches, we clarify the benefits and drawbacks of common methods for modeling panel data, including the GCLM approach we propose. We conclude with a discussion of issues regarding causal inference, including difficulties in separating different types of time-invariant and time-varying effects over time.

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Chidiac, S. E., and F. Mahmoodzadeh. "Constitutive flow models for characterizing the rheology of fresh mortar and concrete." Canadian Journal of Civil Engineering 40, no. 5 (May 2013): 475–82. http://dx.doi.org/10.1139/l2012-025.

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Constitutive equations for fresh mortar and fresh concrete provide the characterization of the mixture’s flow and the quantification of the rheological properties. This paper presents a constitutive material model for mortar and concrete that builds on previous research. It postulates that (a) the shear stress is the sum of three components: static interaction between particles, dynamic interaction between particles, and collision of particles; and (b) the cell is a representative volume of the mixture. For fresh concrete, the effects of particle collisions are negligible due to high concentration, and the equation reduces to the Bingham model. Experimental data reported in the literature was employed to evaluate the predictive capabilities of the constitutive equations. The model results are found to compare very well with the measured experimental data and the difference is within the measurement errors.

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Danner, Daniel, Dirk Hagemann, Daniel V. Holt, Marieke Hager, Andrea Schankin, Sascha Wüstenberg, and Joachim Funke. "Measuring Performance in Dynamic Decision Making." Journal of Individual Differences 32, no. 4 (January 2011): 225–33. http://dx.doi.org/10.1027/1614-0001/a000055.

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The Tailorshop simulation is a computer-based dynamic decision-making task in which participants lead a fictional company for 12 simulated months. The present study investigated whether the performance measure in the Tailorshop simulation is reliable and valid. The participants were 158 employees from different companies. Structural equation models were used to test τ-equivalent measurement models. The results indicate that the trends of the company value between the second and the twelfth month are reliable variables. Furthermore, this measure predicted real-life job performance ratings by supervisors and was associated with the performance in another dynamic decision-making task. Thus, the trend of the company value provides a reliable and valid performance indicator for the Tailorshop simulation.

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Gilles, Damien, and Ghyslaine McClure. "Measured natural periods of concrete shear wall buildings: insights for the design of Canadian buildings." Canadian Journal of Civil Engineering 39, no. 8 (August 2012): 867–77. http://dx.doi.org/10.1139/l2012-074.

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Structural engineers routinely use rational dynamic analysis methods for the seismic analysis of buildings. In linear analysis based on modal superposition or response spectrum approaches, the overall response of a structure (for instance, base shear or inter-storey drift) is obtained by combining the responses in several vibration modes. These modal responses depend on the input load, but also on the dynamic characteristics of the building, such as its natural periods, mode shapes, and damping. At the design stage, engineers can only predict the natural periods using eigenvalue analysis of structural models or empirical equations provided in building codes. However, once a building is constructed, it is possible to measure more precisely its dynamic properties using a variety of in situ dynamic tests. In this paper, we use ambient motions recorded in 27 reinforced concrete shear wall (RCSW) buildings in Montréal to examine how various empirical models to predict the natural periods of RCSW buildings compare to the periods measured in actual buildings under ambient loading conditions. We show that a model in which the fundamental period of RCSW buildings varies linearly with building height would be a significant improvement over the period equation proposed in the 2010 National Building Code of Canada. Models to predict the natural periods of the first two torsion modes and second sway modes are also presented, along with their uncertainty.

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Kumar, M. Rohin, and C. Venkatesan. "Effects of blade configuration parameters on helicopter rotor structural dynamics and whirl tower loads." Aeronautical Journal 120, no. 1224 (February 2016): 271–90. http://dx.doi.org/10.1017/aer.2015.11.

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ABSTRACTThe influence of the blade geometric parameters on the structural dynamic characteristics, response and loads of a helicopter rotor under hover condition in a whirl tower was investigated. A general geometry was considered for the rotor blade which included configuration parameters like root offset, torque offset, pre-twist, pre-cone, pre-droop, pre-sweep, tip-sweep and tip-anhedral. The option of placing concentrated masses at any location on the blade was also included. Natural frequencies and the corresponding mode shapes of the rotating blade were obtained by solving the linear, undamped structural dynamics model in the finite element domain. For calculating the response and loads on the rotor, the complete aeroelastic equation was solved in modal space. Aerodynamic models used in the aeroelastic loads calculations were Peters-He dynamic wake theory for inflow and themodifiedONERA dynamic stall theory for airloads calculations. From the study, the blade structural dynamic characteristics are found to be sensitive to variation in blade geometric parameters. Tip-sweep was found to have significant effects on root oscillatory moments. The moments at the tip junction with the straight portion of the blade were found to be substantially affected by tip-sweep and tip-anhedral.

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SHAO, XIAO, and LI H. CHAI. "A STATISTICAL DYNAMIC APPROACH TO STRUCTURAL EVOLUTION OF COMPLEX CAPITAL MARKET SYSTEMS." International Journal of Modern Physics B 25, no. 13 (May 20, 2011): 1807–21. http://dx.doi.org/10.1142/s021797921110031x.

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As an important part of modern financial systems, capital market has played a crucial role on diverse social resource allocations and economical exchanges. Beyond traditional models and/or theories based on neoclassical economics, considering capital markets as typical complex open systems, this paper attempts to develop a new approach to overcome some shortcomings of the available researches. By defining the generalized entropy of capital market systems, a theoretical model and nonlinear dynamic equation on the operations of capital market are proposed from statistical dynamic perspectives. The US security market from 1995 to 2001 is then simulated and analyzed as a typical case. Some instructive results are discussed and summarized.

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Riganti, Gianmario, and Ezio Cadoni. "Multiple Pseudo-Plastic Appearance of the Dynamic Fracture in Quasi-Brittle Materials." Materials 13, no. 21 (November 5, 2020): 4976. http://dx.doi.org/10.3390/ma13214976.

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Understanding and simulating the dynamic response of quasi-brittle materials still remains as one of the most challenging issues in structural engineering. This paper presents the damage propagation material model (DAMP) developed in order to obtain reliable results for use in structural engineering practice. A brief overview focuses on the differences between fracture mechanics studies, and engineering material modelling is presented to highlight possible guideline improvements. An experimental dynamic test performed on ultra-high-performance concrete specimens was used to obtain evidence of the physical behaviour of brittle materials with respect to specimen size variations and, consequently, to verify the reliability of the material equations proposed. Two widely used material models (RHT and M72R3), as representatives of the classical brittle material models for structural purposes, and the proposed material model are compared. Here, we show how: (i) the multiple structural strength of brittle materials arises from the damage propagation process, (ii) there is no contradiction between fracture mechanics and the engineering approach once the velocity of damage propagation is chosen as fundamental material property and (iii) classical dynamic material models are intrinsically not objective with related loss of predictive capability. Finally, the original material model equation and the experimental strategy, dedicated to its extended verification, will be shown in order to increase the design predictiveness in the dynamic range considering structure and specimen size variations. The dynamic stress increasing factor (DIF), experimentally observed and widely recognised in literature as a fundamental concept for quasi-brittle material modelling, has been reviewed and decomposed in its geometrical and material dependencies. The new material model defines its DIF starting from the physical quantities of the damage propagation velocity applied to the test case boundary conditions. The resultant material model predictiveness results improved greatly, demonstrating its ability to model several dynamic events considering size and dynamic load variations with a unique material property set without showing contradictions between numerical and experimental approaches.

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Hall, E., S. Kessler, and S. Hanagud. "Use of Fractal Dimension in the Characterization of Chaotic Structural Dynamic Sytems." Applied Mechanics Reviews 44, no. 11S (November 1, 1991): S107—S113. http://dx.doi.org/10.1115/1.3121342.

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The purpose of this paper is to investigate the use of fractal dimensions in the characterization of chaotic systems in structural dynamics. The investigation focuses on the example of a simply-supported, Euler-Bernoulli beam which when subjected to a transverse forcing function of a particular amplitude responds chaotically. Three different nonlinear models of the system are studied: a complex partial differential equation (PDE) model, a simplified PDE model, and a Galerkin approximation to the simpler PDE model. The responses of each model are examined through zero velocity Poincare´ sections. To characterize and compare the chaotic trajectories, the box counting fractal dimension of the Poincare´ sections are computed. The results demonstrate that the fractal dimension is a spatial invariant along the length of the beam for the specific class of forcing function studied, and thus it can be used to characterize chaotic motions. In addition, the three models yield different fractal dimensions for the same forcing which indicates that fractal dimensions can also be used to quantify whether a simplification of a chaotic model accurately predicts the chaotic behavior of the full-blown model. Thus the conclusion of the paper is that fractal dimensions may play an important role in the characterization of chaotic structural dynamic systems.

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Barauskas, Rimantas, Andrius Kriščiūnas, and Tomas Blažauskas. "A finite element model in a form of structural dynamic equation for the transient analysis of pressure in pipelines." Journal of Vibroengineering 18, no. 2 (March 31, 2016): 1209–26. http://dx.doi.org/10.21595/jve.2016.16609.

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The finite element model of transient pressure pulse propagation in a pipeline is presented in the form of the standard structural dynamic equation, which combines steady flow analysis for obtaining the initial conditions of the flow in the form of pressures and flow rates and non-linear dynamic analysis by using explicit numerical integration techniques. Three options of simplification of governing equation set have been analyzed. At low values of steady flow speed many non-linear and convection terms could be omitted, while at the flow speeds comparable with the wave propagation speed the full equation system has been analyzed. The full equation system analysis involves the techniques ensuring corrections of the initial conditions and of the nodal flow rate balance. The investigated pipelines may contain large number of branches and loops. Parts of large pipelines are analyzed as separate sub-models by employing non-reflecting boundary conditions at the cut boundaries. Properties of pressure pulse front degradation as it propagates through branching points of the pipeline can be examined.

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Toroptsev, E. L., A. S. Marakhovskii, and R. R. Duszynski. "The problem of digitalization of the dynamic input-output model." Economic Analysis: Theory and Practice 16, no. 5 (May 28, 2020): 946–72. http://dx.doi.org/10.24891/ea.19.5.946.

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Subject. The article addresses the digitalization of the dynamic model of inter industry balance. Objectives. We focus on developing our own statistical research base for input-output analysis, structural forecasting, sustainability, economic dynamics and economic growth. Mathematically, the study is formalized by the Cauchy problem for ordinary differential equations. Methods. The methodology components include theoretical and practical bases of the systems, statistical, input-output, and structural dynamic analysis. Results. Based on official statistics, we solved the problem of digitalization of the dynamic model of input-output balance, written in the form of a system of differential equations. For the first time, this model was transferred from a set of purely theoretical structures to a class of computable models. We developed a sequence of coordinated actions and calculations, which serve as a methodology for the said transfer. We also devised and presented the elements of our own statistical research base. Conclusions. The quantitative measurement of the dynamic inter-industry model in the form of a system of differential equations opens up broad perspectives on the sustainability of macroeconomics, its structural readiness for expanded reproduction, i.e. economic growth. The model can be used both independently and in combination with equilibrium and other agent-oriented models.

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Fan, Xue Ping, and Yue Fei Liu. "Time-Dependent Reliability Prediction of Bridge Member Based on MGPF and SHM Data." Advanced Engineering Forum 15 (February 2016): 119–32. http://dx.doi.org/10.4028/www.scientific.net/aef.15.119.

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In the long-term monitoring period, the structural health monitoring (SHM) system produces a huge amount of monitoring data. It becomes a very important thing that how to real-timely predict structural reliability indices from such huge number of monitored data. In this paper, To real-timely predict reliability of bridge members with real-time monitoring information, with the long-term mass monitored data of health monitoring system, the data-based dynamic model including observation equation and state equation is built, and then the mixed Gaussian particle filter (MGPF) is introduced. With particle filter method, Bayesian method and dynamic model, the posteriori distribution parameters of state variable and one-step forward prediction distribution parameters of monitored data are predicted. Through resampling technique, with MGPF, the prediction precision of dynamic model can generally increase. Based on the dynamic monitored data, the weights of resampled particles can be constantly updated. Therefore the problem of particle degradation is solved. Finally based on the real-time predicted distribution parameters, with the first order second moment (FOSM) method, the dynamic reliability of bridge member is predicted, and an actual example is provided to illustrate the application and feasibility of the proposed models and methods.

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Miguel, Pablo Martínez de, Carmen De-Pablos-Heredero, Jose Luis Montes, and Antón García. "Impact of Dynamic Capabilities on Customer Satisfaction through Digital Transformation in the Automotive Sector." Sustainability 14, no. 8 (April 15, 2022): 4772. http://dx.doi.org/10.3390/su14084772.

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Technology has impacted businesses in different areas, and, consequently, many companies have found it necessary to make changes in their structures and business models to improve customer satisfaction. The objective was to quantify the effect of dynamic capabilities on customer satisfaction, through digital transformation within the automotive sector. A random sample of 42 questionnaires on 127 surveyed industries was collected during the period 2019–2020 in a pre-COVID-19 context. A structural equation model (SEM) in two stages was applied. In the first stage, two reflective models were built. In a second stage, a structural equation model was evaluated. The results obtained in this study showed that the capabilities of sensing, seizing and innovation were suitably grouped in a construct called “Dynamic Capabilities”. A positive influence of Dynamic Capabilities on customer satisfaction was found. Therefore, the companies in this industry should focus on developing dynamic capabilities to improve customer satisfaction. Once the opportunities have been identified, managers take advantage of their potential (seizing) to transform and exploit knowledge in the creation, innovation, process improvement, and definition of strategies to combine new knowledge with that already existing. The digital transformation has contributed to identify the real needs for customers, to contact them and solve their problems, as well as offering products and services by anticipating their needs.

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Pickering, Carolyn, Maria Yefimova, Danny Wang, Christopher Maxwell, and Rita Jablonski. "PROGRESSIVELY LOWERED STRESS THRESHOLD FOR BEHAVIORAL SYMPTOMS OF DEMENTIA: A DYNAMIC STRUCTURAL EQUATION MODEL." Innovation in Aging 6, Supplement_1 (November 1, 2022): 50. http://dx.doi.org/10.1093/geroni/igac059.193.

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Abstract The progressively lowered stress threshold model suggests that due to impairments in coping, persons living with dementia have a reduced threshold for stress and respond with more behavioral symptoms of dementia as stress accumulates throughout the day. While the propositions of the model have not been evaluated, this model serves as the basis of non-pharmacological interventions for behavioral symptom management aimed at modifying the environment to reduce stressors. These interventions have mixed success, which may be due to traditional longitudinal measurement models that don’t account for the dynamic temporal nature of behavioral symptoms. This paper evaluates the progressively lowered stress threshold conceptual model as an explanation for behavioral symptoms of dementia and tests several of its hypothesized propositions using an intensive longitudinal design. A sample of N=165 family caregivers completed brief daily diary surveys for 21 days (n=2841) reporting on behavioral symptoms of their care recipients. Dynamic structural equation modeling was used as the analytic technique to examine the impact of caregiver and care recipient environmental stressors on the diversity of behavioral symptoms of dementia (number of different symptoms) to account for the nested data structure and autoregressive relationships. Results show direct relationships between environmental stressors and diversity of behavioral symptoms of dementia that same day and the following day. Findings provide support for the progressively lowered stress threshold model. Further, findings suggest an extension to the conceptual model is warranted given evidence of an exposure/recovery trajectory and the lagged effects of stress exposure on behavioral symptoms of dementia presentation.

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Xu, Ran, Richard P. DeShon, and Christopher R. Dishop. "Challenges and Opportunities in the Estimation of Dynamic Models." Organizational Research Methods 23, no. 4 (May 6, 2019): 595–619. http://dx.doi.org/10.1177/1094428119842638.

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Interest in modeling longitudinal processes is increasing rapidly in organizational science. Organizational scholars often employ multilevel or hierarchical linear models (HLMs) to study such processes given that longitudinal data in organizational science typically consist of observations over a relatively small number of time intervals ( T) nested within a relatively large number of units ( N; e.g., people, teams, organizations). In this paper, we first distinguish change and dynamics as common research foci when modeling longitudinal processes and then demonstrate that a unique set of inferential hazards exists when investigating change or dynamics using multilevel models. Specifically, multilevel models that include one or more time-lagged values of the dependent variable as predictors often result in substantially biased estimates of the model parameters, inflated Type I error rates, and ultimately inaccurate inference. Using Monte Carlo simulations, we investigate the bias and Type I error rates for the standard centered/uncentered hierarchical linear model (HLM) and compare them with two alternative estimation methods: the Bollen and Brand structural equation modeling (SEM) approach and the Arrelano and Bond generalized method of moments using instrumental variables (GMM-IV) approach. We find that the commonly applied hierarchical linear model performs poorly, whereas the SEM and GMM-IV approaches generally perform well, with the SEM approach yielding slightly better performance in small samples with large autoregressive effects. We recommend the Bollen and Brand SEM approach for general use when studying change or dynamics in organizational science.

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Lesko, S. A., A. S. Alyoshkin, and V. V. Filatov. "Stochastic and Percolating Models of Blocking Computer Networks Dynamics during Distribution of Epidemics of Evolutionary Computer Viruses." Russian Technological Journal 7, no. 3 (June 9, 2019): 7–27. http://dx.doi.org/10.32362/2500-316x-2019-7-3-7-27.

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The paper presents a complex model of the dynamics of virus epidemies propagation in computer networks, based on topological properties of computer networks and mechanisms of the viruses spread. On one hand, this model is based on the use of percolation theory methods, which makes it possible to determine such structural-information characteristics of networks as the dependence of the percolation threshold on the average number of connections per one node (network density). On the other hand, the dynamic processes of stochastic propagation in computer networks of evolving viruses are observed when anti-virus programs become outdated and postponed. The paper discusses the concept of percolation threshold, provides an equation for the dependence of the percolation threshold of a network on its density obtained by analyzing numerical simulation data. The dynamics of virus epidemies were studied through two approaches. The first one is based on the description of transition diagrams between states of nodes, after which a system of kinetic differential equations for the virus epidemies is constructed. The second is based on considering the probabilities of transitions between possible states of the entire network. A second-order differential equation is obtained in this article, and a boundary value problem is formulated. Its solution describes the dependence of the network blocking probability on the blocking probability of an individual node. The solution also makes it possible to estimate the time required to reach the percolation threshold. The model incorporates the evolutionary properties of viruses: previously immunized or disinfected nodes can be infected again after a certain time interval. Besides, the model incorporates a lag of the anti-virus protection. Analysis of the solutions obtained for the models created shows the possibility of various modes of virus propagation. Moreover, with some sets of values of differential equation coefficients, an oscillating and almost periodic nature of virus epidemies is observed, which largely coincides with real observations.

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Zhou-Bowers, S., and D. C. Rizos. "B-Spline Impulse Response Functions of Rigid Bodies for Fluid-Structure Interaction Analysis." Advances in Civil Engineering 2018 (October 11, 2018): 1–10. http://dx.doi.org/10.1155/2018/9760361.

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Reduced 3D dynamic fluid-structure interaction (FSI) models are proposed in this paper based on a direct time-domain B-spline boundary element method (BEM). These models are used to simulate the motion of rigid bodies in infinite or semi-infinite fluid media in real, or near real, time. B-spline impulse response function (BIRF) techniques are used within the BEM framework to compute the response of the hydrodynamic system to transient forces. Higher-order spatial and temporal discretization is used in developing the kinematic FSI model of rigid bodies and computing its BIRFs. Hydrodynamic effects on the massless rigid body generated by an arbitrary transient acceleration of the body are computed by a mere superposition of BIRFs. Finally, the dynamic models of rigid bodies including inertia effects are generated by introducing the kinematic interaction model to the governing equation of motion and solve for the response in a time-marching scheme. Verification examples are presented and demonstrate the stability, accuracy, and efficiency of the proposed technique.

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Castro-Schilo, Laura, and Eric Russo. "Fitting Structural Equations Models with Interactive and Dynamic Tools in JMP® Pro." Structural Equation Modeling: A Multidisciplinary Journal 28, no. 5 (March 16, 2021): 794–806. http://dx.doi.org/10.1080/10705511.2020.1854764.

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Allison, Paul D., Richard Williams, and Enrique Moral-Benito. "Maximum Likelihood for Cross-lagged Panel Models with Fixed Effects." Socius: Sociological Research for a Dynamic World 3 (January 1, 2017): 237802311771057. http://dx.doi.org/10.1177/2378023117710578.

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Panel data make it possible both to control for unobserved confounders and allow for lagged, reciprocal causation. Trying to do both at the same time, however, leads to serious estimation difficulties. In the econometric literature, these problems have been solved by using lagged instrumental variables together with the generalized method of moments (GMM). Here we show that the same problems can be solved by maximum likelihood (ML) estimation implemented with standard software packages for structural equation modeling (SEM). Monte Carlo simulations show that the ML-SEM method is less biased and more efficient than the GMM method under a wide range of conditions. ML-SEM also makes it possible to test and relax many of the constraints that are typically embodied in dynamic panel models.

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Ye, Ai, Kathleen M. Gates, Teague Rhine Henry, and Lan Luo. "Path and Directionality Discovery in Individual Dynamic Models: A Regularized Unified Structural Equation Modeling Approach for Hybrid Vector Autoregression." Psychometrika 86, no. 2 (April 11, 2021): 404–41. http://dx.doi.org/10.1007/s11336-021-09753-6.

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Popkov, Yu S. "A New Class of Dynamic Macrosystem Models with Self-Reproduction." Environment and Planning A: Economy and Space 21, no. 6 (June 1989): 739–51. http://dx.doi.org/10.1068/a210739.

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The author considers a class of macrosystems where the relaxation time of the distribution process of elements is significantly less than the relaxation time of the self-reproduction process. The proposed model of such macrosystems defines the system of differential equations with nonlinearity generated by the solution of a mathematical programming problem with an entropy objective function. Methods for the structural analysis of this model are considered, and applications to demographic modelling, biological dynamics, and chemical kinetics are given.

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TASKINOGLU, EZGI S., and JOSETTE BELLAN. "A posteriori study using a DNS database describing fluid disintegration and binary-species mixing under supercritical pressure: heptane and nitrogen." Journal of Fluid Mechanics 645 (February 9, 2010): 211–54. http://dx.doi.org/10.1017/s0022112009992606.

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A large eddy simulation (LES) a posteriori study is conducted for a temporal mixing layer which initially contains different species in the lower and upper streams and in which the initial pressure is larger than the critical pressure of either species. A vorticity perturbation, initially imposed, promotes roll-up and a double pairing of four initial spanwise vortices to reach a transitional state. The LES equations consist of the differential conservation equations coupled with a real-gas equation of state, and the equations utilize transport properties depending on the thermodynamic variables. Unlike all LES models to date, the differential equations contain, additional to the subgrid-scale (SGS) fluxes, a new SGS term denoted a ‘pressure correction’ (p correction) in the momentum equation. This additional term results from filtering the Navier–Stokes equations and represents the gradient of the difference between the filtered p and p computed from the filtered flow field. A previous a priori analysis, using a direct numerical simulation (DNS) database for the same configuration, found this term to be of leading order in the momentum equation, a fact traced to the existence of regions of high density-gradient magnitude that populated the entire flow; in that study, the appropriateness of several SGS-flux models was assessed, and a model for the p-correction term was proposed.In the present study, the constant-coefficient SGS-flux models of the a priori investigation are tested a posteriori in LES devoid of, or including, the SGS p-correction term. A new p-correction model, different from that of the a priori study, is used, and the results of the two p-correction models are compared. The results reveal that the former is less computationally intensive and more accurate than the latter in reproducing global and structural features of the flow. The constant-coefficient SGS-flux models encompass the Smagorinsky (SMC) model, in conjunction with the Yoshizawa (YO) model for the trace, the gradient (GRC) model and the scale similarity (SSC) models, all exercised with the a priori study constant-coefficient values calibrated at the transitional state. Further, dynamic SGS-flux model LESs are performed with the p correction included in all cases. The dynamic models are the Smagorinsky (SMD) model, in conjunction with the YO model, the gradient (GRD) model and ‘mixed’ models using SMD in combination with GRC or SSC utilized with their theoretical coefficient values. The LES comparison is performed with the filtered-and-coarsened DNS (FC-DNS) which represents an ideal LES solution. The constant-coefficient models including the p correction (SMCP, GRCP and SSCP) are substantially superior to those devoid of it; the SSCP model produces the best agreement with the FC-DNS template. For duplicating the local flow structure, the predictive superiority of the dynamic mixed models is demonstrated over the SMD model; however, even better predictions in capturing vortical features are obtained with the GRD model. The GRD predictions improve when LES is initiated at a time past the initial range in which the p-correction term rivals in magnitude the leading-order term in the momentum equation. Finally, the ability of the LES to predict the FC-DNS irreversible entropy production is assessed. It is shown that the SSCP model is the best at recovering the domain-averaged irreversible entropy production. The sensitivity of the predictions to the initial conditions and grid size is also investigated.

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Westcott, Gregory, Annette R. Grilli, Stephan Grilli, James T. Kirby, and Fengyan Shi. "INDIVIDUAL WAVE EFFECTS ON COASTAL STRUCTURE DAMAGE DURING WINDSTORMS." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 14. http://dx.doi.org/10.9753/icce.v36.structures.14.

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In hazard assessment studies that evaluate the damage caused to coastal structures by windstorm-generated surge and waves, the standard approach has been to estimate structural loading by applying phase-averaged wave propagation models (e.g., SWAN, STWAVE) and storm surge models (e.g., ADCIRC), coupled or not with each other. Bare-earth â€œDigital Elevation Modelsâ€ (DEMs) have typically been used as a basis for model grid development, with sometimes empirical adjustments being made to beach profiles or dune crest levels to account for storm-induced erosion. In recent work, the latter approach has been improved by including real time morphodynamic changes in simulations, using models such as XBeach (e.g., Schambach 2017; Schambach et al., 2017), which are still based on the wave action conservation equation, including semi-empirical parameterizations of wave breaking and many formulations based on linear wave theory (e.g., phase/group velocity, radiation stresses,â€¦), as well as low-order wave-wave interaction terms. Finally, structural damage has typically been estimated based on empirical damage curves, developed based on field surveys, that use flow depth and controlling wave crest height as inputs (e.g., Grilli et al., 2017). Neglected in this modeling approach, however, are dynamic set-up and runup effects, as well as strongly nonlinear wave interactions that occur near and in the surf and swash zones.

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WANG, YI JIAO, QING YI FENG, and LI HE CHAI. "STRUCTURAL EVOLUTIONS OF STOCK MARKETS CONTROLLED BY GENERALIZED ENTROPY PRINCIPLES OF COMPLEX SYSTEMS." International Journal of Modern Physics B 24, no. 30 (December 10, 2010): 5949–71. http://dx.doi.org/10.1142/s0217979210055457.

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As one of the most important financial markets and one of the main parts of economic system, the stock market has become the research focus in economics. The stock market is a typical complex open system far from equilibrium. Many available models that make huge contribution to researches on market are strong in describing the market however, ignoring strong nonlinear interactions among active agents and weak in reveal underlying dynamic mechanisms of structural evolutions of market. From econophysical perspectives, this paper analyzes the complex interactions among agents and defines the generalized entropy in stock markets. Nonlinear evolutionary dynamic equation for the stock markets is then derived from Maximum Generalized Entropy Principle. Simulations are accordingly conducted for a typical case with the given data, by which the structural evolution of the stock market system is demonstrated. Some discussions and implications are finally provided.

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Xu, Yi Cheng, Feng Li Cao, Guo Zhang Li, and Jing Tao Zhou. "Analysis on Torsional Vibration Characteristics of Tracked Vehicle Gearbox." Applied Mechanics and Materials 401-403 (September 2013): 354–57. http://dx.doi.org/10.4028/www.scientific.net/amm.401-403.354.

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According to the dynamic characteristics of tracked vehicle gearbox system, the integrated influence of elasticity of shaft, gear meshing stiffness and transmission error in the system is considered, and mathematics models of two type configurations are created, Matlab/Simulink model of which are provided. The torsional vibration dynamic model of transmission system with tracked vehicle gearbox is developed and the vibration equation of the system is established. The influences of the transmission errors, moment of inertia, mesh phase and torsion stiffness are investigated respectively. It has important realistic meaning for guiding the gearbox structural design and improving, reducing its fault rate.

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Chu, Jiangtao, and Yue Yang. "Linking Structural Equation Modelling with Bayesian Network and Coastal Phytoplankton Dynamics in Bohai Bay." E3S Web of Conferences 38 (2018): 01028. http://dx.doi.org/10.1051/e3sconf/20183801028.

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Bayesian networks (BN) have many advantages over other methods in ecological modelling and have become an increasingly popular modelling 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 modelling (SEM). In this method, SEM is used to improve the model structure for BN. This method was used to simulate coastal phytoplankton dynamics in 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 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, despite the Redfield ratio indicating that phosphorus should be the primary nutrient limiting factor, our results indicate that silicate plays the most important role in regulating phytoplankton dynamics in Bohai Bay.

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Journal articles on the topic 'Dynamic structural equation models'

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