Simple Model of Frequency-Dependent Impedance Functions in Soil-Structure Interaction Using Frequency-Independent Elements

This study presents a methodology to make a simple equivalent model of frequency-dependent impedance functions of soil-structure interactions using a frequency-independent spring and dashpot, together with a proposed element called “gyromass.” The gyromass is frequency independent and is defined as a unit system that generates a reaction force due to the relative acceleration of the nodes between which the gyromass is placed. It is found that a model consisting of a spring, dashpot, and gyromass may generate various types of frequency-dependent impedance characteristics. This study proposes two types of simple models that express typical frequency-independent impedance functions of soil-structure interactions by using the gyromass. The advantage of these models is that the frequency-dependent characteristics can easily be expressed by a small number of elements and degrees of freedom. Moreover, they can be applied directly to conventional time-history analyses, even beyond the elastic region of the structural members. An example in which a simple model is applied to the time-history analysis of a soil-pile-superstructure system with an inelastic structural member when subjected to an earthquake wave is illustrated.     

Simplified Model for Vertical Vibrations of Surface Foundations

A simplified model for simulating unbounded soil in the vertical vibration problems of surface foundations is presented. The model comprises a mass, a spring, and a dashpot without any internal degree of freedom. By considering three equivalent criteria, a group of equivalent models is established for a foundation-soil system. An optimal equivalent model is then determined to represent the best simplified model. The parameters of the optimal equivalent model may be obtained by a much easier and more direct method than the optimization technique used by existing models. The dynamic responses of the foundation-soil system using the optimal equivalent models are also compared with those obtained by the half-space theory and by the existing lumped-parameter models. The optimal equivalent model is found to have more accurate results than existing discrete models especially for responses at resonant frequencies. This proposed method may be easily applied to practical problems involving soil-structure interaction such as machine foundation vibration and seismic structural analysis.     

The equivalence of regression models using difference scores and models using separate scores for each informant: Implications for the study of informant discrepancies.

Research on informant discrepancies has increasingly utilized difference scores. This article demonstrates the statistical equivalence of regression models using difference scores (raw or standardized) and regression models using separate scores for each informant to show that interpretations should be consistent with both models. First, regression equations were used to demonstrate that difference score models are equivalent to models using separate scores for each informant. Second, a hypothesis-driven empirical example (218 mother–child dyads, mean age = 11.5 years, 49% female participants, 49% White, 47% African American) was used to provide an illustration of the equivalence of the 2 models. Implications of the equivalence of models using difference scores and models using separate scores for each informant are discussed in terms of the growing prevalence of an interpretation in the literature of difference score analyses that is inconsistent with results from equivalent separate informant analyses. Differences in the separate predictive ability of informants should be acknowledged as an alternative interpretation of the difference score regression coefficient. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Structural Health Monitoring by Piezo-Impedance Transducers. I: Modeling

The electromechanical impedance (EMI) technique, which employs piezoelectric–ceramic lead–zirconate–titarate (PZT) patches as impedance transducers, has emerged as a powerful nondestructive evaluation technique during the last few years. This series of two papers present a new simplified methodology to diagnose structural damages by means of surface bonded piezo-impedance transducers. The first part introduces a new PZT–structure electroelastic interaction model based on the concept of “effective impedance.” The proposed formulations can be conveniently employed to extract the mechanical impedance of any “unknown” structural system from the admittance signatures of a surface bonded PZT patch. This is an improvement over the existing models, whose complexity prohibits direct application in similar practical scenarios. This also eliminates the requirement of any a priori information concerning the phenomenological nature of the structure. The proposed model is experimentally verified by means of test on a smart system comprising an aluminum block with a PZT patch instrumented on it. Part II of this paper outlines a new methodology to evaluate structural damages using the extracted impedance spectra. The proposed approach is found to be suitable for diagnosing damages in structures ranging from miniature precision machine and aerospace components to large civil structures.     

Toward an Alternative Representation for Disentangling Age-Associated Differences in General and Specific Cognitive Abilities.

Much of cognitive aging research concerns whether age-associated differences in various cognitive performances can be accounted for by general explanatory constructs or whether several specific processes are involved. Structural equation models have been proposed to disentangle general and specific age-associated differences in cognitive performance. This article demonstrates that existing methods that employ stepwise procedures run the risk of biasing results toward general resource accounts. An alternative model representation (i.e., the nested factor model) is proposed that affords simultaneous estimation of general and specific effects and is applied to data from the Berlin Aging Study. Using the nested factor model allowed the authors to detect that specific group factors explained 25% of the age-associated variance in addition to the general factor. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Model for Predicting Performance of Architects and Engineers

Certain attributes of an architect or engineer (AE) may be used to predict his performance. These attributes may be categorized as “hard” or “soft” attributes. Hard attributes include an AE’s cognitive ability, job knowledge, task proficiency, and job experience. Soft attributes include an AE’s conscientiousness, initiative, social skills, controllability, and commitment. The purpose of this study is to identify those attributes that affect an AE’s performance, and to construct a model to predict his performance in design build (DB) projects. Twenty five attributes were generated using the hierarchy tree. The importance of these attributes was tested with designer/ builders who select and hire AEs, using a standard questionnaire. A statistical test showed that 24 of these attributes are significantly important. Thirty AEs were evaluated by experienced designer/builders (experts) who have worked with them in completed DB projects. Besides giving a global performance score of the AE (dependent variable), each expert also evaluated the AE on the degree to which they exhibited the important attributes (independent variables). Based on these ratings, an optimum multiple regression performance prediction model was obtained. To validate the model, another group of experts used the optimum model to evaluate 18 other AEs. The resulting performance score as calculated by the model was compared to the global performance scores awarded by the designer/builders. This validation process showed the model to be robust. The results of the study reveal that an AE’s performance can be predicted by using just three attributes: AE’s problem solving ability and project approach, AE’s speed in producing design drawings, and the AE’s level of enthusiasm in tackling a difficult assignment.     

Depth-Dependent Dispersion Coefficient for Modeling of Vertical Solute Exchange in a Lake Bed under Surface Waves

Variable pressure at the sediment/water interface due to surface water waves can drive advective flows into or out of the lake bed, thereby enhancing solute transfer between lake water and pore water in the lake bed. To quantify this advective transfer, the two-dimensional (2D) advection-dispersion equation in a lake bed has been solved with spatially and temporally variable pressure at the bed surface. This problem scales with two dimensionless parameters: a “dimensionless wave speed” (W) and a “relative dispersivity” (λ). Solutions of the 2D problem were used to determine a depth-dependent “vertically enhanced dispersion coefficient” (DE) that can be used in a 1D pore-water quality model which in turn can be easily coupled with a lake water quality model. Results of this study include a relationship between DE and the depth below the bed surface for W>50 and λ ? 0.1. The computational results are compared and validated against a set of laboratory measurements. An application shows that surface waves may increase the sediment oxygen uptake rate in a lake by two orders of magnitude.     

Bayesian Updating of Structural Models and Reliability using Markov Chain Monte Carlo Simulation

In a full Bayesian probabilistic framework for “robust” system identification, structural response predictions and performance reliability are updated using structural test data D by considering the predictions of a whole set of possible structural models that are weighted by their updated probability. This involves integrating h(θ)p(θ∣D) over the whole parameter space, where θ is a parameter vector defining each model within the set of possible models of the structure, h(θ) is a model prediction of a response quantity of interest, and p(θ∣D) is the updated probability density for θ, which provides a measure of how plausible each model is given the data D. The evaluation of this integral is difficult because the dimension of the parameter space is usually too large for direct numerical integration and p(θ∣D) is concentrated in a small region in the parameter space and only known up to a scaling constant. An adaptive Markov chain Monte Carlo simulation approach is proposed to evaluate the desired integral that is based on the Metropolis-Hastings algorithm and a concept similar to simulated annealing. By carrying out a series of Markov chain simulations with limiting stationary distributions equal to a sequence of intermediate probability densities that converge on p(θ∣D), the region of concentration of p(θ∣D) is gradually portrayed. The Markov chain samples are used to estimate the desired integral by statistical averaging. The method is illustrated using simulated dynamic test data to update the robust response variance and reliability of a moment-resisting frame for two cases: one where the model is only locally identifiable based on the data and the other where it is unidentifiable.     

A dual-process model of the alcohol–behavior link for social drinking.

A dual-process model of the alcohol–behavior link is presented, synthesizing 2 of the major social–cognitive approaches: expectancy and myopia theories. Substantial evidence has accrued to support both of these models, and recent neurocognitive models of the effects of alcohol on thought and behavior have provided evidence to support both as well. While proponents of these theories have not suggested that they are mutually exclusive views on how alcohol affects behavior, attempts to synthesize the 2 have been conspicuously absent. The dual-process model presented suggests that the alcohol–behavior link is better reconceptualized as involving a “preconsumption” and a “consumption” phase. This is achieved in the context of contemporary models of automaticity in social behavior, emphasizing the commonality of both controlled and automatic processes in drinking-related behavior. It is argued that a complete understanding of the alcohol–behavior link requires an appreciation of the ways in which the mind may become “intoxicated” even in the absence of alcohol consumption. Suggestions for further research in this area, testing the present dual-process model of the alcohol–behavior link, are also discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Quantitative Structural Health Monitoring by Ultrasonic Guided Waves

This paper presents a global-local (GL) method to simulate the interaction of ultrasonic guided waves with structural defects in isotropic and multilayered composite platelike structures. The GL method uses a full finite-element (FE) discretization of the defected region to properly represent wave diffraction phenomena and a suitable set of wave functions to simulate regions away from the joint. Displacement and stress continuity conditions are imposed at the boundary between the global and the local regions. The radiated wave field can be then calculated by using standard techniques (least-squares method). The novelty of the proposed approach over previous GL techniques is the use of semianalytical FE (SAFE) modeling for the “global” simulation. The SAFE method, which only requires the discretization of the waveguide’s cross section, allows handling complex structures (multilayered composites, arbitrary cross sections, etc.) in a computationally efficient manner. Applications of the GL method to damage quantification will be shown for the cases of notches in aluminum plates and delaminationlike defects in aircraft composite panels.     

Masking misfit in confirmatory factor analysis by increasing unique variances: A cautionary note on the usefulness of cutoff values of fit indices.

Fit indices are widely used in order to test the model fit for structural equation models. In a highly influential study, Hu and Bentler (1999) showed that certain cutoff values for these indices could be derived, which, over time, has led to the reification of these suggested thresholds as “golden rules” for establishing the fit or other aspects of structural equation models. The current study shows how differences in unique variances influence the value of the global chi-square model test and the most commonly used fit indices: Root-mean-square error of approximation, standardized root-mean-square residual, and the comparative fit index. Using data simulation, the authors illustrate how the value of the chi-square test, the root-mean-square error of approximation, and the standardized root-mean-square residual are decreased when unique variances are increased although model misspecification is present. For a broader understanding of the phenomenon, the authors used different sample sizes, number of observed variables per factor, and types of misspecification. A theoretical explanation is provided, and implications for the application of structural equation modeling are discussed. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Three-Dimensional Electromechanical Impedance Model for Multiple Piezoceramic Transducers—Structure Interaction

In the last few decades, piezoceramic (PZT) transducers have been extensively used either as actuators or as sensors in the vibration and noise control of aero, civil, and mechanical (ACM) systems. Only in the last decade, PZT transducers have been used in the electromechanical impedance (EMI) models as both sensor and actuator for the structural health monitoring of ACM systems. In the EMI models, the PZT transducers are generally surface bonded to the host structure and are then subjected to one-dimensional (1D) voltage to interrogate the structure for the desired frequency range. The interrogation results in the prediction of electromechanical admittance signatures. These signatures serve as indicators of the health/integrity of the structure. However, the existing single PZT–structure interaction models consider the PZT transducer to be negligible in mass and thus ignored. Moreover, they impose restrictions on the PZT shape, size, and isotropy. This paper presents a novel semianalytical multiple three-dimensional PZT–structure interaction model which considers the “mass” of the PZT transducers, and the transducers are subjected to parallel (1D) sinusoidal voltage. Further, the model does not impose restriction on the shape (square or rectangular), size (thin or thick), and electrical properties (isotropic or anisotropic) of PZT. The derived model is also experimentally verified using lab-sized aluminum plate. As it is generic, the model is expected to be applicable for the nondestructive evaluation of most ACM systems.     

Role of the Material Constitutive Model in Simulating the Reusable Launch Vehicle Thrust Cell Liner Response

The reusable launch vehicle thrust cell liner, or thrust chamber, is a critical component of the space shuttle main engine. It is designed to operate in some of the most severe conditions seen in engineering practice. These conditions give rise to characteristic deformations of the cooling channel wall exposed to high thermal gradients and a coolant-induced pressure differential, characterized by the wall’s bulging and thinning, which ultimately lead to experimentally observed “dog-house” failure modes. In this paper, these deformations are modeled using the cylindrical version of the higher-order theory for functionally graded materials in conjunction with two inelastic constitutive models for the liner’s constituents, namely Robinson’s unified viscoplasticity theory and the power-law creep model. Comparison of the results based on these two constitutive models under cyclic thermomechanical loading demonstrates that, for the employed constitutive model parameters, the power-law creep model predicts more precisely the experimentally observed deformation leading to the “dog-house” failure mode for multiple short cycles, while also providing much improved computational efficiency. The differences in the two models’ predictions are rooted in the differences in the short-term creep and relaxation responses.     

A model of motor inhibition for a complex skill: Baseball batting.

The ability to inhibit an ongoing action in response to a signal from the environment is important for many perceptual-motor actions. This paper examines a particular example of this behavior: attempting to inhibit or “check” a swing in baseball batting. A model of motor inhibition in batting is proposed. In the model there are three different inhibition signals (out of range launch angle, early expected-actual trajectory discrepancy, and late expected-actual trajectory discrepancy) resulting in four possible response outcomes for the batter’s swing (full swing, inhibited swing, partial response, or interrupted swing). The predictions of the model were compared with the actual batting performance of 20 baseball players using a high-fidelity batting simulator. The proportions of the different response outcomes could be explained by the inhibition model for 17/20 of the batters in the study. These findings suggest that models of motor inhibition developed for simple, discrete tasks can be applied to complex, multistage behaviors. This batting inhibition model could be used to provide a quantitative measure of a player’s bat control for training and player-screening purposes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Detection of Changes in Global Structural Stiffness Coefficients Using Acceleration Feedback

This technical note presents an extension of a previous study where two methods for detecting structural damage have been developed by using displacement and velocity measurements. In this study, acceleration feedback is used in detecting changes in global structural stiffness coefficients of lumped-mass-shear-beam models. The previously developed method relies on the decoupling of effects of changes in stiffness at different locations and the use of displacement or velocity feedback has proven to be effective. Extension to the use of acceleration feedback using existing formulation is not trivial in that the desired decoupling effect cannot be achieved by simple coordinate transformation because the acceleration itself is directly related to the stiffness coefficients. An approach to circumvent this difficulty is presented and it involves increasing the order of time derivatives of the linear system so that the acceleration becomes the “velocity” of the new system. The performance of the proposed method is demonstrated using an illustrative example of a three-story model with stiffness changes at different floors. Numerical studies are also conducted to evaluate the time horizons required to normalize monitor outputs for the effective and efficient detection of stiffness changes.     

Random effects probit and logistic regression models for three-level data

In analysis of binary data from clustered and longitudinal studies, random effect models have been recently developed to accommodate two-level problems such as subjects nested within clusters or repeated classifications within subjects. Unfortunately, these models cannot be applied to three-level problems that occur frequently in practice. For example, multicenter longitudinal clinical trials involve repeated assessments within individuals and individuals are nested within study centers. This combination of clustered and longitudinal data represents the classic three-level problem in biometry. Similarly, in prevention studies, various educational programs designed to minimize risk taking behavior (e.g., smoking prevention and cessation) may be compared where randomization to various design conditions is at the level of the school and the intervention is performed at the level of the classroom. Previous statistical approaches to the three-level problem for binary response data have either ignored one level of nesting, treated it as a fixed effect, or used first- and second-order Taylor series expansions of the logarithm of the conditional likelihood to linearize these models and estimate model parameters using more conventional procedures for measurement data. Recent studies indicate that these approximate solutions exhibit considerable bias and provide little advantage over use of traditional logistic regression analysis ignoring the hierarchical structure. In this paper, we generalize earlier results for two-level random effects probit and logistic regression models to the three-level case. Parameter estimation is based on full-information maximum marginal likelihood estimation (MMLE) using numerical quadrature to approximate the multiple random effects. The model is illustrated using data from 135 classrooms from 28 schools on the effects of two smoking cessation interventions.     

Dynamic Performance Simulation of Long-Span Bridge under Combined Loads of Stochastic Traffic and Wind

Slender long-span bridges exhibit unique features which are not present in short and medium-span bridges such as higher traffic volume, simultaneous presence of multiple vehicles, and sensitivity to wind load. For typical buffeting studies of long-span bridges under wind turbulence, no traffic load was typically considered simultaneously with wind. Recent bridge/vehicle/wind interaction studies highlighted the importance of predicting the bridge dynamic behavior by considering the bridge, the actual traffic load, and wind as a whole coupled system. Existent studies of bridge/vehicle/wind interaction analysis, however, considered only one or several vehicles distributed in an assumed (usually uniform) pattern on the bridge. For long-span bridges which have a high probability of the presence of multiple vehicles including several heavy trucks at a time, such an assumption differs significantly from reality. A new “semideterministic” bridge dynamic analytical model is proposed which considers dynamic interactions between the bridge, wind, and stochastic “real” traffic by integrating the equivalent dynamic wheel load (EDWL) approach and the cellular automaton (CA) traffic flow simulation. As a result of adopting the new analytical model, the long-span bridge dynamic behavior can be statistically predicted with a more realistic and adaptive consideration of combined loads of traffic and wind. A prototype slender cable-stayed bridge is numerically studied with the proposed model. In addition to slender long-span bridges which are sensitive to wind, the proposed model also offers a general approach for other conventional long-span bridges as well as roadway pavements to achieve a more realistic understanding of the structural performance under probabilistic traffic and dynamic interactions.     

On the likelihood ratio test in structural equation modeling when parameters are subject to boundary constraints.

The authors show how the use of inequality constraints on parameters in structural equation models may affect the distribution of the likelihood ratio test. Inequality constraints are implicitly used in the testing of commonly applied structural equation models, such as the common factor model, the autoregressive model, and the latent growth curve model, although this is not commonly acknowledged. Such constraints are the result of the null hypothesis in which the parameter value or values are placed on the boundary of the parameter space. For instance, this occurs in testing whether the variance of a growth parameter is significantly different from 0. It is shown that in these cases, the asymptotic distribution of the chi-square difference cannot be treated as that of a central chi-square-distributed random variable with degrees of freedom equal to the number of constraints. The correct distribution for testing 1 or a few parameters at a time is inferred for the 3 structural equation models mentioned above. Subsequently, the authors describe and illustrate the steps that one should take to obtain this distribution. An important message is that using the correct distribution may lead to appreciably greater statistical power. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Behavioral science, engineering, and poetry revisited.

Forty years ago, Lehrman (1971) identified 2 orientations to the study of animal behavior. The natural history orientation conducted field and lab research designed to reveal how animals cope with the circumstances of their natural environment. Such research reveals the diversity among different types of animals and differences between the world of animals and the world of humans (i.e., “poetry”). In contrast, the anthropocentric orientation studies animals either to generate animal-derived general laws applicable to humans or to provide experimental information that, for ethical and practical reasons, cannot be acquired from human research. The primary motivation for the anthropocentric orientation is to provide workable models for investigating specifically human problems (i.e., “engineering”). Evidence is presented from the study of bird song that demonstrates the contribution that the “poetic” approach can make to anthropocentric (“engineering”) concerns. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Nonlinear System Modeling and Velocity Feedback Compensation for Effective Force Testing

Effective force testing (EFT) is a test procedure that can be used to apply real-time earthquake loads to large-scale structural models. The implementation of the EFT method requires velocity feedback compensation for the actuators in order to apply forces accurately to test structures. Nonlinearities in the servosystem have a significant impact on the velocity feedback compensation and test results when large flow demands are present, which can be caused by large structural velocities and/or large forces applied to the test structure. This paper presents a nonlinear servosystem model, upon which a nonlinear compensation scheme is proposed. The model and compensation scheme are experimentally verified. The results indicate that the proposed model accurately describes the servosystem behavior, and with the nonlinear velocity feedback compensation, real-time dynamic testing can be conducted using the EFT method.